# Gidel High-Performance Imaging & Vision Solutions > Official technical documentation and product index for Gidel, a global leader in high-performance FPGA-based imaging and vision solutions. This file contains detailed specifications for our complete portfolio of PCIe Frame Grabbers (Camera Link, CoaXPress, GigE Vision, and User-Defined Protocols), Edge AI Vision Systems (NVIDIA Jetson + FPGA), and Ultra-Compact FPGA Modules. It also covers our real-time image processing technologies, including SkyBoost (Aerial RAW to JPG Acceleration), SkyBoost-RT (Real-Time Aerial RAW to JPG Processing), and Compression IPs (Lossless, JPEG, Quality+). Additionally, it details our Camera Link and CoaXPress Camera Simulators, deterministic Image Acquisition Systems, Multi-Camera Vision Systems, and the ProcVision development suite for full Imaging & Vision ISP customization. > PCIe Frame Grabbers: Camera Link CoaXPress-12 GigE Vision (10, 40, 100+ GigE) User-Defined Protocols & custom options Edge AI Vision Systems (FantoVision) FantoVision: NVIDIA Jetson plus FPGA integrated systems for edge acquisition and real-time processing via 10GigE, CoaXPress-12, and Camera Link. Ultra-Compact FPGA Modules (Tiny) Embedded FPGA modules for custom imaging pipelines and system integration Real-Time Processing Technologies Full ISP pipelines, image enhancement, HDR Compression IPs: Lossless, JPEG, Quality+ SkyBoost: Batch RAW to JPG acceleration SkyBoost-RT: Real-time RAW to JPG processing Camera Simulation and Deterministic Replay Camera Link and CoaXPress camera simulators Deterministic, reproducible input streams for validation and debug Multi-camera synchronization and repeatable workloads Development and Customization ProcVision SDK and tools for implementing custom FPGA algorithms and proprietary IP ## Pages - [Solutions](https://gidel.com/solutions/) - [test](https://gidel.com/test/) - [Accessibility Statement](https://gidel.com/accessibility-statement/): Accessibility Statement Gidel Gidel is committed to ensuring digital accessibility for all visitors. This Accessibility Statement outlines how Gidel is... - [Custom FPGA Solutions](https://gidel.com/custom-fpga-solution/): Gidel’s Custom FPGA Solutions include both application-specific and open infrastructure solutions with tremendous flexibility to meet diverse compute acceleration and... - [Support](https://gidel.com/support-gidel/): Gidel support plays a critical role because our products are often key elements in customer systems. For this reason, we... - [About Us](https://gidel.com/about-us/): For over 30 years, Gidel has delivered high-performance FPGA-based imaging and vision solutions. We help customers solve complex imaging challenges... - [News & Events](https://gidel.com/news-and-events/): News & Event blog, featuring Gidel’s latest FPGA-based vision & imaging technology developments, releases, and coming events. - [Contact Us](https://gidel.com/contact-us/): Reach out to Gidel to discuss your Imaging and Vision requirements and learn how our FPGA-based acceleration solutions can enhance... - [Powering Real-Time Imaging & Vision Systems](https://gidel.com/): Real-Time Frame Grabber Solutions for Imagin & Vision Applications Gidel develops advanced FPGA-based frame grabber solutions to boost your high-performance... - [Privacy Policy & Cookie Policy](https://gidel.com/privacy-policy/): Privacy Policy Last Updated On: 28-Nov-2025Effective Date: 28-Nov-2025 This privacy policy describes how Gidel Ltd. collects, uses, and discloses your... ## Posts - [VISION 2026: FantoVision for Aerospace & Defence](https://gidel.com/vision-2026-gidel-aerospace-defence-innovation/): Gidel’s FantoVision Mini Edge AI & FPGA Systems have been selected as a VISION Guided Tours Innovation in Aerospace &... - [Meet Gidel at VISION Show 2026](https://gidel.com/vision-show-2026-gidel/): Meet Gidel at VISION Show 2026 and explore FPGA imaging solutions for real-time acquisition, image processing, compression, and Edge AI.... - [Camera Link Cameras: Connectivity, Performance, Integration & Selection](https://gidel.com/camera-link-cameras/): Selecting the right Camera Link camera involves more than resolution and frame rate. Learn about Base, Medium, Full, and 80-bit... - [GigE Vision Cameras: Connectivity, Performance, Integration & Selection](https://gidel.com/gige-vision-cameras/): Selecting the right GigE Vision camera involves more than resolution and frame rate. Learn about 1, 2. 5, 5, and... - [CoaXPress Cameras: Connectivity, Performance, Integration & Selection](https://gidel.com/coaxpress-cameras/): Selecting the right CoaXPress camera involves more than resolution and frame rate. Learn about CXP-6 and CXP-12 configurations, multi-link bandwidth,... - [Gidel Launches SkyBoost to Accelerate Aerial Photogrammetry Workflows](https://gidel.com/skyboost-accelerating-aerial-photogrammetry-post-processing/): High-resolution aerial mapping missions can generate thousands of RAW images that take hours or even days to process. Discover how... - [SkyBoost-RT Wins VSD 2026 Innovators Award for Real-Time Aerial Imaging](https://gidel.com/real-time-aerial-imaging-processing-skyboost-rt-award/): Gidel SkyBoost-RT has been recognized as a Vision Systems Design 2026 Innovators Awards Silver Honoree. This real-time aerial imaging processing... - [Gidel at IMVC 2026](https://gidel.com/israel-machine-vision-conference-imvc-2026-gidel/): At IMVC 2026, Gidel demonstrated FPGA imaging solutions featuring embedded AI vision, multi-sensor CoaXPress-12 acquisition, FPGA processing, Quality+ Compression, and... - [Gidel at Embedded Technologies 2026](https://gidel.com/meet-gidel-at-embedded-technologies-conference-2026/): At Embedded Technologies 2026, Gidel demonstrated FPGA-based imaging and embedded AI vision solutions. The FantoVision Edge AI platform combined 10... - [Gidel at ChipEx 2026 Exhibition](https://gidel.com/chipex2026-exhibition/): At ChipEx 2026, Gidel demonstrated FantoVision20-GigE with real-time 10 GigE Vision acquisition, single-exposure HDR, Quality+ Compression, and sub-frame FPGA processing.... - [Gidel 2025 Milestones in FPGA Imaging and Edge AI](https://gidel.com/gidel-2025-milestones-edge-ai-vision/): Gidel’s 2025 milestones included three new FantoVision FPGA Edge AI systems, advances in high-resolution acquisition and low-latency imaging, Quality+ Compression... - [Breaking the Jetson I/O Wall: Gidel’s FPGA-Powered Edge AI Vision Systems](https://gidel.com/edge-ai-vision-system/): Gidel expands FantoVision with three dedicated Edge AI Vision Systems for CoaXPress-12, 10 GigE Vision, and Camera Link. By combining... - [Gidel at Vision & AI 2025](https://gidel.com/meet-gidel-at-vision-and-ai-2025/): At Vision & AI 2025, Gidel demonstrated FantoVision20-GigE with real-time 10 GigE Vision acquisition, HDR, and FPGA compression, together with... - [Meeting the Challenges of High-Resolution Outdoor Imaging](https://gidel.com/meeting-the-challenges-of-high-resolution-outdoor-imaging/): High-resolution outdoor imaging faces critical challenges: extreme lighting, massive data streams, and strict SWaP limits. Discover how the partnership between... - [Gidel at UVID 2025](https://gidel.com/meet-gidel-at-uvid-2025-uav-defense-innovation-exhibition/): At UVID 2025, Gidel demonstrated FPGA imaging for UAV, defense, and airborne systems with FantoVision20-GigE, real-time 10 GigE Vision acquisition,... - [Gidel at the Military & Aviation Exhibition 2025](https://gidel.com/meet-gidel-at-the-military-aviation-exhibition-fpga-imaging-solutions/): At the Military & Aviation Exhibition 2025, Gidel demonstrated FPGA-based airborne imaging systems for UAV, ISR, EO/IR, and tactical applications.... - [Improving Performance in Low Latency Vision Systems Without Added Latency](https://gidel.com/low-latency-system-fpga/): Low latency vision systems must increase throughput without sacrificing responsiveness, determinism, or power efficiency. See how FPGA acceleration and hybrid... - [Gidel at the Defense Solutions Exhibition 2025](https://gidel.com/defense-solutions-exhibition/): At the Defense Solutions Exhibition 2025, Gidel demonstrated real-time FPGA imaging for defense using FantoVision20-GigE, with 10 GigE Vision acquisition,... - [Gidel at ChipEx 2025](https://gidel.com/chipex2025-exhibition/): At the ChipEx 2025 Exhibition, Gidel demonstrated FantoVision20-GigE with real-time 10 GigE Vision acquisition, single-frame HDR, Quality+ Compression, and deterministic... - [Gidel at Vision China 2025](https://gidel.com/vision-china-2025/): At Vision China 2025 in Shanghai, Gidel demonstrated FPGA-based machine vision technologies including FantoVision Edge AI, CoaXPress-12 acquisition, real-time HDR,... - [Gidel at IMVC 2025](https://gidel.com/join-us-at-imvc-2025-gidel/): At IMVC 2025, Gidel demonstrated FPGA imaging and Edge AI technologies including real-time CoaXPress-12 acquisition, HDR, Quality+ Compression, high-bandwidth processing,... - [Gidel Quality+ Compression Award 2025: inVISION Top Innovation](https://gidel.com/gidel-quality-plus-compression-top-innovation-2025/): Gidel Quality+ Compression received inVISION Top Innovation 2025 recognition for real-time FPGA compression with 1:10+ data reduction, more than 1.... - [Gidel 2024 Milestones: FPGA Imaging, Edge Computing & Global Growth](https://gidel.com/2024-a-year-of-innovation-and-milestones-gidel/): Explore the Gidel 2024 Milestones, including advances in modular FPGA imaging, rugged edge computing platforms, global expansion, and more than... - [Gidel at Military & Aviation 2024](https://gidel.com/military-aviation-2024/): At Military & Aviation 2024, Gidel demonstrated FPGA-based imaging and Edge AI technologies for defense and aerospace, including high-speed acquisition,... - [AI Breast Cancer Screening Device Uses Gidel’s FantoVision](https://gidel.com/breast-cancer-screening-device-thermomind-case-study/): ThermoMind Vision One is an AI breast cancer screening device that combines multimodal thermal, NIR, and 3D imaging with Gidel... - [Gidel at Embedded World 2024](https://gidel.com/gidel-embedded-vision-platform-embedded-world-2024/): At Embedded World 2024 in Nuremberg, Gidel demonstrated FantoVision embedded vision systems with FPGA-based acquisition, NVIDIA Jetson Edge AI, real-time... - [Edge Imaging Webinar: Overcoming Bandwidth Limits at the Edge](https://gidel.com/webinar-overcoming-bandwidth-limitations-when-imaging-on-the-edge/): In this Edge Imaging webinar, Gidel CTO Reuven Weintraub explains how FPGA acquisition, FantoVision Edge AI Systems, and real-time compression... - [Gidel Adds CXP-12 Support to Its CoaXPress Simulator](https://gidel.com/gidel-camsim-camera-simulator-now-supports-cxp-12-interface/): Gidel expands CamSim-X with CXP-12 support, enabling 12. 5 Gb/s CoaXPress simulation for high-bandwidth frame grabber development, validation, and system... - [Gidel FantoVision Wins 2023 Vision Systems Design Award for Edge Computer Vision](https://gidel.com/fantevision-edge-computer-vision-award-2023/): Gidel FantoVision received a 2023 Vision Systems Design Silver Award for Edge Computer Vision. The platform combines high-bandwidth FPGA acquisition... - [High-Speed Image Acquisition and Gigapixel Processing in Vision Systems](https://gidel.com/high-speed-image-acquisition/): High-speed image acquisition can generate several gigapixels per second, creating major bandwidth and processing challenges. Learn how FPGA acquisition, preprocessing,... - [First Heterogeneous Embedded Vision Systems Combining Jetson and FPGA](https://gidel.com/embedded-vision-system-fantovision20-40/): Gidel integrates the NVIDIA Jetson Orin NX 16GB into the FantoVision series, creating a breakthrough heterogeneous embedded vision system. With... - [Enabling High-Speed AOI Machines in Mail Sorting](https://gidel.com/enabling-high-speed-aoi-machines-for-sorting-applications/): Discover how a leading mail sorting manufacturer leveraged Gidel’s FPGA-based vision infrastructure to optimize high-speed AOI Machines. By integrating the... - [High-Quality Image Compression: Compressing Image Data, Not Image Quality](https://gidel.com/compressing-image-data-not-image-quality/): As modern sensors drive data rates to gigapixel levels, standard codecs often sacrifice detail for bandwidth. This article explores how... - [FPGA Wireless Research Powered by Gidel Technology](https://gidel.com/fpga-wireless-research/): Discover how TU Berlin utilizes Gidel technology in their latest FPGA wireless research to enable real-time Massive MIMO processing. This... - [FantoVision20 Embedded Computer Vision Platform for 20 Gb/s Processing](https://gidel.com/embedded-computer-vision-fantovision-20/): Discover FantoVision20, an ultra-compact embedded computer vision system combining NVIDIA Jetson computing with Altera Arria 10 FPGA acquisition and processing.... - [Stratix 10 NX Module and PCIe Board for AI and Vector Processing](https://gidel.com/stratix-10-nx-fpga-module/): Gidel’s Proc10N FPGA Module and Proc1C10N PCIe Board bring Stratix 10 NX AI Tensor Blocks, 400 GB/s HBM2 throughput, and... - [FPGA vs GPU | Is This the End of FPGA?](https://gidel.com/fpga-vs-gpu-interview/): Explore the FPGA vs GPU debate through insights from Gidel’s CTO. Learn where FPGA architectures can offer advantages in deterministic... - [FPGA Debugging Tools for Image Processing with CertifEye](https://gidel.com/fpga-image-processing-certifeye/): Discover how CertifEye accelerates FPGA debugging and image-processing validation by enabling engineers to inject test images, verify FPGA IP, analyze... - [First 100Gb/s CoaXPress Frame Grabber with 8 × CXP-12 Links](https://gidel.com/news-cxp-12-frame-grabber-8-link-100gbps/): Gidel introduces a 100Gb/s CoaXPress frame grabber with 8 CXP-12 links, on-board Lossless/JPEG compression, deep buffering, and customizable FPGA processing... - [Gidel Introduces New FPGA JPEG Compression IP](https://gidel.com/jpeg-fpga-compression-ip/): Gidel, a technology leader in FPGA-based Vision and Imaging solutions, today announced a new real-time JPEG Compression IP. This compact... - [Gidel Launches Real-Time Reversible Compression IP](https://gidel.com/fpga-reversible-compression-ip/): Gidel, a technology leader in high-performance accelerators utilizing FPGAs, today announced a new Reversible Compression IP. This breakthrough solution reduces... - [FPGA Acceleration Powers CHREC’s Reconfigurable Supercomputer](https://gidel.com/fpga-acceleration-chrec-supercomputer/): Discover how CHREC utilized Gidel’s FPGA acceleration technology to build Novo-G, the world’s fastest research-focused reconfigurable supercomputer. Learn how our... - [Gidel Powers New 360 Degree Camera Solution for VR and AR](https://gidel.com/360-degree-camera-system/): Discover how Gidel’s InfiniVision technology powers next-gen VR with a fully synchronized 24-camera array. Learn how our scalable FPGA architecture... ## Products - [SkyBoost](https://gidel.com/product/skyboost-fastest-raw-to-jpg-acceleration/): Product Overview SkyBoost is a workstation-grade acceleration solution designed to eliminate post-processing bottlenecks by performing high-volume and high quality RAW... - [SkyBoost-RT](https://gidel.com/product/skyboost-rt-aerial-imaging/): Product Overview SkyBoost-RT is a dedicated solution for real-time aerial imaging and similar applications, designed to accelerate End-to-End processing directly... - [ProcFG](https://gidel.com/product/image-acquisition-system-procfg/): ProcFG: Deterministic Image Acquisition System ProcFG is Gidel’s deterministic image acquisition system, engineered to reliably capture every frame produced by... - [Proc1C10N-CXP12](https://gidel.com/product/octo-cxp-12-frame-grabber/): 8-Link CXP-12 Frame Grabber for CoaXPress Cameras The Proc1C10N-CXP12 is a high-performance eight-link CXP-12 frame grabber designed for real-time image... - [FantoVision20-GigE](https://gidel.com/product/jetson-gige/): Jetson with Dual 10 GigE Vision Frame Grabber The FantoVision20-GigE is a rugged Jetson system with a fully integrated GigE... - [FantoVision40-CXP12](https://gidel.com/product/jetson-coaxpress/): Jetson with Quad CoaXPress-12 Frame Grabber The FantoVision40-CXP12 is a rugged Jetson system with a fully integrated CoaXPress-12 frame grabber.... - [FantoVision20-CL](https://gidel.com/product/jetson-camera-link/): Jetson with Camera Link Frame Grabber The FantoVision20-CL is a rugged Jetson system with a fully integrated Camera Link frame... - [CamSim-X](https://gidel.com/product/coaxpress-simulator/): Camera Simulator for CoaXPress The CamSim-X is a high-performance CoaXPress camera simulator that supports up to four CoaXPress-12 output links... - [ProcWizard](https://gidel.com/product/fpga-programming-sdk/): FPGA Programming SDK Gidel’s FPGA Programming SDK streamlines development by offering both Board Support Packages (BSPs) and Application Support Packages... - [HDR Correction](https://gidel.com/product/high-dynamic-range-hdr-ip/): HDR IP Correction: High Performance Single Exposure While traditional HDR relies on multiple exposures — a method often impractical for... - [ProcVision Suite](https://gidel.com/product/modular-vision-sdk-for-fpga/): Modular Vision SDK for FPGA Development Gidel’s ProcVision Suite is a Modular Vision SDK for FPGA Development. It provides a... - [Proc1C10N](https://gidel.com/product/proc1c10n-fpga-accelerator/): Proc1C10N: AI-Optimized FPGA Accelerator with HBM2 Technology The Proc1C10N™ is a compact, ultra-high-performance FPGA accelerator built on Altera Stratix® 10... - [Proc1C10M](https://gidel.com/product/proc1c10m-accelerator-card/): Proc1C10M – High-Performance FPGA Accelerator Card with HBM2 Technology The Proc1C10M™ is a compact, ultra-high-performance accelerator card built on Altera... - [Proc10A-40GigE](https://gidel.com/product/proc10a-40-gige-card-smart-nic/): 4 × 10 GigE Frame Grabber Card for GigE Vision Cameras The Proc10A-40GigE is a high-performance 40 GigE Vision frame... - [Quality+ Compression](https://gidel.com/product/improved-snr-real-time-lossless-compression/): FPGA Image Compression for High-Bandwidth Imaging Gidel’s Quality+ is a proprietary FPGA image compression IP developed as a high-performance alternative... - [HawkEye-20GigE](https://gidel.com/product/hawkeye-20gige-vision-frame-grabber/): 2-Port 10 GigE Frame Grabber for GigE Vision Cameras The HawkEye-20GigE is a high-performance 20 GigE Vision frame grabber designed... - [JPEG Compression](https://gidel.com/product/jpeg-encoder/): JPEG Encoder on FPGA for High-Speed Imaging Gidel’s JPEG encoder performs real-time image compression directly on the FPGA, enabling high-speed... - [LL Compression](https://gidel.com/product/fpga-lossless-image-compression/): Lossless Image Compression on FPGA for High-Speed Imaging Gidel’s Lossless Image Compression IP targets FPGA-based Imaging & Vision applications. This... - [CamSim-CL](https://gidel.com/product/camera-link-simulator/): Camera Simulator for Camera Link The CamSim-CL is a high-performance Camera Link simulator that supports Base, Medium, Full, Deca, and... - [FDB Modules](https://gidel.com/product/tiny-fpga-modules/): FDB Series: Tiny FPGA Modules for High-Performance Embedded Systems The FDB series includes FDB16 (49 × 54 mm), FDB27 (58... - [Proc10M](https://gidel.com/product/small-fpga-module/): Proc10M: Small FPGA Module for High-Performance Embedded Systems The Proc10M™ is a compact, high-performance FPGA module designed for embedded and... - [Proc10N](https://gidel.com/product/fpga-for-ai/): Proc10N: Compact FPGA for AI and High-Performance Embedded Systems The Proc10N™ is a compact FPGA for AI module powered by... - [HawkEye](https://gidel.com/product/low-power-accelerator-board/): HawkEye: Low Power Accelerator Board The HawkEye™ is a low-profile, low power accelerator board built on Altera Arria 10 GX... - [Proc10S](https://gidel.com/product/proc10s-accelerator-board/): Proc10S: Accelerator Board The Proc10S™ is a high-performance, scalable accelerator board built on Altera Stratix® 10 GX FPGA technology. Designed... - [InfiniVision](https://gidel.com/product/multi-camera-vision-system/): InfiniVision: Scalable Multi-Camera Acquisition System InfiniVision is a high-performance multi-camera system that powers Gidel’s scalable image acquisition platform, enabling synchronized... - [Proc1C10M-120GigE](https://gidel.com/product/proc1c10m-100gige-frame-grabber/): 12 × 10 GigE Frame Grabber for GigE Vision Cameras The Proc1C10M-120GigE is a high-performance 100 GigE Vision frame grabber... - [Proc1C10N-120GigE](https://gidel.com/product/proc1c10n-100-gige-vision-frame-grabber/): 12 × 10 GigE AI Frame Grabber for GigE Vision Cameras The Proc1C10N-120GigE is a high-performance 100 GigE Vision frame... - [HawkEye-CL](https://gidel.com/product/camera-link-frame-grabber/): High-Performance Frame Grabber for Camera Link Cameras The HawkEye-CL is a high-performance Camera Link frame grabber designed for real-time acquisition... - [Proc10A-CXP](https://gidel.com/product/proc10a-cxp-6-frame-grabber/): 8-Link CXP-6 Frame Grabber for CoaXPress Cameras The Proc10A-CXP is a high-performance eight-link CXP-6 frame grabber designed for real-time image... - [HawkEye-CXP12](https://gidel.com/product/hawkeye-coaxpress-12-frame-grabber/): 4-Link CXP-12 Frame Grabber for CoaXPress Cameras The HawkEye-CXP12 is a high-performance four-link CoaXPress-12 frame grabber designed for real-time image... - [Proc10A](https://gidel.com/product/fpga-accelerator-card/): Proc10A: High-Performance FPGA Accelerator Card The Proc10A™ is a flexible, high-performance, low-power FPGA accelerator card built on Altera’s Arria® 10... - [FantoVision40](https://gidel.com/product/jetson-frame-grabber/): Jetson with CoaXPress-12 & 10 GigE Frame Grabbers The FantoVision40 is a rugged Jetson frame grabber system with fully integrated... - [FantoVision20](https://gidel.com/product/jetson-dual-interface-frame-grabber/): Jetson with 10 GigE Vision & Camera Link Frame Grabbers The FantoVision20 is a rugged Jetson system with a fully... ## Applications - [UAV / Drone Computer Vision Systems](https://gidel.com/application/drone-computer/): Drone Computer for Imaging & Vision Applications A drone computer must process data instantly. UAV missions demand low latency and... - [Volumetric Imaging & Augmented Reality Solutions](https://gidel.com/application/volumetric-imaging-augmented-reality/): Gidel provides a modular FPGA-based vision infrastructure designed to support real-time volumetric imaging and augmented reality applications. These systems enable... - [High-Speed Solutions for Optical Sorting Machines](https://gidel.com/application/sorting-machines/): Scalable Vision Architecture for Optical Sorting Machines Modern optical sorting machines depend on advanced vision architectures to deliver high accuracy... - [Modular Medical Imaging Solutions](https://gidel.com/application/modular-medical-imaging/): Gidel delivers advanced medical imaging solutions built on FPGA-based image acquisition and processing architectures. These solutions address the demanding requirements... - [Embedded FPGA Solutions for Embedded Vision](https://gidel.com/application/embedded-fpga-solutions-for-embedded-vision/): Gidel’s embedded FPGA solutions address the growing demand for high-performance, compact, and power-efficient embedded systems. Gidel delivers a broad portfolio... - [Defense Imaging Solutions](https://gidel.com/application/defense-imaging-solutions/): Gidel builds FPGA-based defense imaging solutions on a modular vision architecture that supports high-performance, mission-critical defense applications. These systems deliver... - [Automation Vision in Automatic Test Equipment](https://gidel.com/application/automation-vision-automatic-test-equipment/): Automation Vision enables modern Automatic Test Equipment (ATE) to test electronic systems and components with high precision. As a result,... - [High-Performance Imaging & Vision Solutions](https://gidel.com/application/vision-imaging-solutions/): Gidel’s imaging solutions empower companies to deliver high-performance, real-time vision systems. With over 30 years of FPGA expertise, we combine... # # Detailed Content ## Pages - Published: 2026-05-07 - Modified: 2026-05-28 - URL: https://gidel.com/solutions/ FPGA Solutions for Real-Time Imaging | Gidel Skip to main content Applications Vision & Imaging UAV's / Drones Military & Defense Medical Imaging Sorting Machines Volumetric Imaging Embedded Vision Automatic Test Equipment Solutions PCIe Frame Grabbers GigE Vision HawkEye-20GigE Proc10A-40GigE Proc1C10M-120GigE Proc1C10N-120GigE CoaXPress Proc1C10N-CXP12 HawkEye-CXP12 Proc10A-CXP Camera Link HawkEye-CL Mini Jetson Frame Grabbers FantoVision40 Edge AI FantoVision40-CXP12 FantoVision40 FantoVision20 Edge AI FantoVision20-GigE FantoVision20-CL FantoVision20 Aerial RAW to JPG Acceleration Post-Processing Real-Time Camera Simulators Camera Link CoaXPress Mini Powerful FPGA Modules FDB Proc10M Proc10N FPGA Imaging Libraries Image Compression JPEG Lossless Quality+ HDR Correction Customization options Image Acquisition Systems Multi-Camera Acquisition Deterministic Image Acquisition FPGA Compute Accelerators HawkEye Proc10A Proc1C10M Proc1C10N Proc10S Recording & Streaming Modular Solutions Development Tools Support About Us News & Events Contact Us Search Press ESC to close Popular Searches FPGA Frame Grabber PCIe Machine Vision CoaXPress Browse by Category Products Applications Support News & Events No results found Try different keywords or browse our categories above. 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Applications Overview Vision & Imaging UAV's / Drones Military & Defense Medical Imaging Sorting Machines Volumetric Imaging Embedded Vision Automatic Test Equipment Solutions Overview PCIe Frame Grabbers Overview GigE Vision Overview HawkEye-20GigE Proc10A-40GigE Proc1C10M-120GigE Proc1C10N-120GigE CoaXPress Overview Proc1C10N-CXP12 HawkEye-CXP12 Proc10A-CXP Camera Link Overview HawkEye-CL Mini Jetson Frame Grabbers Overview FantoVision40 Edge AI Overview FantoVision40-CXP12 FantoVision40 FantoVision20 Edge AI Overview FantoVision20-GigE FantoVision20-CL FantoVision20 Aerial RAW to JPG Acceleration Overview Post-Processing Real-Time Camera Simulators Overview Camera Link CoaXPress Mini Powerful FPGA Modules Overview FDB Proc10M Proc10N FPGA Imaging Libraries Overview Image Compression Overview JPEG Lossless Quality+ HDR Correction Customization options Image Acquisition Systems Overview Multi-Camera Acquisition Deterministic Image Acquisition FPGA Compute Accelerators Overview HawkEye Proc10A Proc1C10M Proc1C10N Proc10S Recording & Streaming Modular Solutions Development Tools Support About Us News & Events Contact Us +972-4-610-2500 [email protected] Solutions Explore our comprehensive range of FPGA-based imaging and vision solutions. Solutions PRODUCTS PRODUCTS 3 Low Latency Recording & Streaming Solutions 22 Image Acquisition Solutions: ProcFG vs InfiniVision 16 ISP Solutions for Aerial Mapping: SkyBoost-RT vs. SkyBoost 13 PRODUCTS Parent category of product categories CamSim-CL Camera Link Simulator The CamSim-CL is a high-performance Camera Link simulator designed for… View Details CamSim-X CoaXPress Camera Simulator The CamSim-X is a high-performance CoaXPress camera simulator designed… View Details FantoVision20 Jetson Dual Interface Frame Grabber (10GigE & Camera Link) The FantoVision20 is… View Details FantoVision20-CL Jetson Camera Link Frame Grabber System The FantoVision20-CL is a rugged Jetson… View Details FantoVision20-GigE Jetson GigE Vision Frame Grabber System The FantoVision20-GigE is a rugged Jetson… View Details FantoVision40 Jetson Frame Grabber (Quad CoaXPress-12 & 10GigE) The FantoVision40 is a rugged… View Details FantoVision40-CXP12 FantoVision40‑CXP12: Jetson CoaXPress Vision Frame Grabber System The FantoVision40-CXP12 is a rugged… View Details FDB Modules FDB Series: Tiny FPGA Modules for High-Performance Embedded Systems The FDB series… View Details HawkEye Low Power Accelerator Board The HawkEye™ is a low-profile, low power accelerator… View Details HawkEye-20GigE Dual 10 GigE Frame Grabber The HawkEye-20GigE is a high-performance GigE frame… View Details HawkEye-CL Camera Link Frame Grabber The HawkEye-CL is a high-performance Camera Link Frame… View Details HawkEye-CXP12 Quad CoaXPress 12 Frame Grabber The HawkEye-CXP12 is a high-performance Quad CoaXPress… View Details HDR Correction HDR IP Correction: High Performance Single Exposure While traditional HDR relies on… View Details InfiniVision Scalable Multi-Camera Acquisition System InfiniVision is a high-performance multi-camera system that powers… View Details JPEG Compression Gidel’s real-time JPEG encoder delivers high-performance JPEG compression directly on FPGA. This… View Details Lossless Compression Gidel’s lossless Image Compression IP targets FPGA-based Imaging & Vision applications. This… View Details Proc10A High-Performance FPGA Accelerator Card The Proc10A™ is a flexible, high-performance, low-power FPGA… View Details Proc10A-40GigE High-Performance GigE Card Frame Grabber The Proc10A-40GigE is a high-performance GigE card… View Details Proc10A-CXP Octo CXP 6 Frame Grabber with Real-Time Image Processing The Proc10A-CXP is… View Details Proc10M Small FPGA Module for High-Performance Embedded Systems The Proc10M™ is a compact,… View Details Proc10N Compact FPGA for AI and High-Performance Embedded Systems The Proc10N™ is a… View Details Proc10S Accelerator Board The Proc10S™ is a high-performance, scalable accelerator board built on… View Details Proc1C10M – High-Performance FPGA Accelerator Card with HBM2 Technology The Proc1C10M™ is a… View Details Proc1C10M-120GigE 100GigE Frame Grabber for High-Bandwidth Vision Systems The Proc1C10M-120GigE is a high-performance 100GigE… View Details Proc1C10N AI-Optimized FPGA Accelerator with HBM2 Technology The Proc1C10N™ is a compact, ultra-high-performance… View Details Proc1C10N-120GigE 100GigE Vision Frame Grabber for AI & High-Bandwidth Applications The Proc1C10N-120GigE is… View Details Proc1C10N-CXP12 Octo CXP 12 Frame Grabber with Real-Time Image Processing The Proc1C10N-CXP12 is… View Details ProcFG Deterministic Image Acquisition System ProcFG is Gidel’s deterministic image acquisition system, engineered… View Details ProcVision Suite Modular Vision SDK for FPGA Development Gidel’s ProcVision Suite is a Modular… View Details ProcWizard FPGA Programming SDK Gidel’s FPGA Programming SDK streamlines development by offering both… View Details Quality+ Compression Gidel’s Quality+ lossless Compression Alternative for High-Speed Imaging & Vision Gidel’s Quality+… View Details SkyBoost Product Overview SkyBoost is a workstation-grade acceleration solution designed to eliminate post-processing… View Details SkyBoost-RT Product Overview SkyBoost-RT is a dedicated solution for real-time aerial imaging and similar… View Details Need Help Choosing? Our experts can help you find the right product for your specific requirements. Free product consultation Technical specifications review Custom configuration options Volume pricing available Or contact us directly: [email protected] Full Name Email Phone 12 Ha’ilan St., Northern Ind. Zone POB 281, Or Akiva, Israel 3060000 Phone: +972-4-610-2500 North America: +1 617 849 9220 [email protected] EMEA: +972 4 610 2500 [email protected] APAC: +972 4 610 2500 [email protected] Applications Vision & Imaging UAV/Drone Imaging Systems Defense Systems Medical Imaging Sorting Machines Volumetric Imaging Embedded Vision Automatic test equipment Products & Solutions Frame Grabbers Mini Jetson Frame Grabbers Aerial RAW to JPG Acceleration Camera Simulators Mini Powerful FPGA Modules Image Acquisition Systems FPGA Accelerator Cards Gidel Imaging Libraries High Dynamic Range (HDR) IP Compression Options Recording & Streaming Development Tools Support Support Modular solutions Quick Links About Gidel News & Events Privacy Policy & Cookie Policy Accessibility Contact Us Follow us on social media! Contact Us © 2026 Gidel. All Rights Reserved. Quote 0 We are using cookies to give you the best experience on our website. You can find out more about which cookies we are using or switch them off in settings. Accept Reject Close GDPR Cookie Settings Privacy Overview Strictly Necessary Cookies Powered by  GDPR Cookie Compliance Privacy Overview This website uses cookies so that we can provide you with the best user experience possible. Cookie information is stored in your browser and performs functions such as recognising you when you return to our website and helping our team to understand which sections of the website you find most interesting and useful. Strictly Necessary Cookies Strictly Necessary Cookie should be enabled at all times so that we can save your preferences for cookie settings. Enable or Disable Cookies Enabled Disabled Enable All Save Settings - Published: 2025-08-28 - Modified: 2025-11-28 - URL: https://gidel.com/accessibility-statement/ Accessibility Statement Gidel Gidel is committed to ensuring digital accessibility for all visitors. This Accessibility Statement outlines how Gidel is working to make Gidel. com usable and accessible to people with disabilities. Current Status We are in the process of organizing and updating our website to improve accessibility for all users. While accessibility features are not yet fully implemented, we are actively working toward alignment with recognized standards such as the Web Content Accessibility Guidelines (WCAG) 2. 1 AA. To learn about our broader practices, you may visit our Privacy Policy & Cookie Policy. Our Commitment We are committed to the following principles: Providing an inclusive online experience for every user. Reviewing our content, design, and development practices to identify and remove accessibility barriers. Implementing improvements as part of our ongoing website updates. Following industry-recognized standards and consulting WCAG documentation when planning upgrades. (WCAG reference: https://www. w3. org/WAI/standards-guidelines/wcag/) Feedback and Contact Information We welcome your feedback regarding the accessibility of our website. If you experience difficulty accessing any content on Gidel. com, or if you have recommendations for improvement, please contact us: Email: support@gidel. comPhone: +972-4-6102500 We will make every effort to respond promptly and provide the information you need in an accessible format. - Published: 2023-06-28 - Modified: 2026-05-24 - URL: https://gidel.com/custom-fpga-solution/ Gidel’s Custom FPGA Solutions include both application-specific and open infrastructure solutions with tremendous flexibility to meet diverse compute acceleration and Machine Vision possibilities. We offer three levels of custom FPGA solutions, catering to different market needs: A fully developed solution ready for immediate use with options for off-the-shelf modular FPGA modification. Examples of such solutions include edge computer, frame grabbers, and camera simulators. A fully open FPGA solution enabling modifying the data flow and implementing algorithms on the FPGA of Gidel's products, including edge computer, frame grabbers, and accelerator boards. For this type of solution, the Gidel Proc Dev Kit and the Proc Vision suite significantly simplify the development and optimizes system performance. A fully tailored solution based on Gidel’s existing infrastructure and vast R&D experience, including algorithm research and customization for optimized FPGA usage. This option provides users with optimal acquisition capability and subsystem acceleration tailored to their application specifications. - Published: 2023-04-04 - Modified: 2026-03-22 - URL: https://gidel.com/support-gidel/ Gidel support plays a critical role because our products are often key elements in customer systems. For this reason, we provide top-class assistance and continuously improve the quality of our products. Our FPGA-Based solutions meet demanding imaging and vision needs. Our support team helps you adopt them smoothly and keep your system running reliably. We assist you with: • selecting the right technology. • customizing your solution. • integrating our products into your system. • troubleshooting any issues. For modular Imaging and Vision solutions, please contact us. - Published: 2023-04-03 - Modified: 2026-03-22 - URL: https://gidel.com/about-us/ For over 30 years, Gidel has delivered high-performance FPGA-based imaging and vision solutions. We help customers solve complex imaging challenges with precision, flexibility, and modularity. We focus on real-time, high-resolution imaging for advanced applications. These applications require low latency, power efficiency, and custom FPGA-based processing. Customers choose Gidel for mission-critical environments that demand complete imaging systems. Our solutions cover camera interfacing, image enhancement, real-time compression, and HDR. Whether you are building a complete system or adding FPGA capabilities to an existing one, Gidel offers a seamless path. Our portfolio includes Mini Jetson Frame Grabbers, Frame Grabbers for 10, 40, and 100+ GigE Vision, CoaXPress-12, and Camera Link. We also offer Mini FPGA Modules. Customers can buy these products off the shelf or request customized versions. Gidel also provides flexible Development Tools for customers who want to design their own FPGA imaging pipelines. With these tools, engineers can implement custom algorithms, integrate proprietary IP, and build tailored workflows on the FPGA. This approach reduces development effort and shortens time to market. - Published: 2022-11-22 - Modified: 2026-06-15 - URL: https://gidel.com/news-and-events/ News & Event blog, featuring Gidel's latest FPGA-based vision & imaging technology developments, releases, and coming events. - Published: 2022-07-27 - Modified: 2026-06-15 - URL: https://gidel.com/contact-us/ Reach out to Gidel to discuss your Imaging and Vision requirements and learn how our FPGA-based acceleration solutions can enhance your system performance. Our team is ready to answer your questions, provide pricing and technical guidance, and help you choose the ideal solution for your application. - Published: 2022-07-10 - Modified: 2026-07-13 - URL: https://gidel.com/ Real-Time Frame Grabber Solutions for Imagin & Vision Applications Gidel develops advanced FPGA-based frame grabber solutions to boost your high-performance imaging and vision applications. With over 30 years of experience, we serve industries including defense, medical, industrial automation, aerospace, and AI vision. Portfolio: PCIe cards, Mini Vision Edge PCs & FPGA modules & Tools Our frame grabber solutions portfolio includes PCIe Frame Grabbers, Mini Jetson Frame Grabber systems and FPGA development tools. Gidel’s hardware supports 1, 2. 5, 5, 10, 20, 40, and 100+ GigE Vision, CoaXPress, and Camera Link interfaces. We offer compact PCIe boards and ruggedized Nvidia Mini Jetson Frame Grabber Systems for embedded and airborne platforms. Our Edge imaging systems combine an FPGA Frame Grabbers with NVIDIA Jetson Orin and Nvidia Jetson Xavier for powerful, low-latency frame grabber solutions. This makes them ideal for UAVs, drones, and mobile applications where size, weight, and power (SWaP) are critical. Gidel’s systems can capture data from multiple cameras simultaneously, offering up to 40 Gb/s of acquisition bandwidth. We provide real-time image processing on FPGAs, including advanced features such as HDR, white balance, image enhancement, and pre-processing. Our compression options include JPEG, lossless, H. 264, H. 265, and Gidel’s proprietary Quality+ compression, ensuring a superior image-quality-to-compression ratio. Gidel also supports long-duration recording with up to 2 TB SSDs and real-time streaming. This is essential for applications like inspection systems, scientific research, autonomous platforms, and security systems. We design our compact FPGA modules for easy integration and customization. Gidel’s solutions are modular, enabling customers to start with an off-the-shelf platform and expand to support their specific protocols and needs. Whether you require camera protocol adaptation, dataflow customization, or unique AI pipelines, our tools and IPs make it possible. Gidel’s ProcVision Suite and Proc Dev Kit streamline development, offering a powerful environment to test, simulate, and implement your vision system—from acquisition to processing and from software to FPGA integration. We are dedicated to providing reliable, scalable, and innovative frame grabber solutions. Whether for machine vision, volumetric video, medical diagnostics, or autonomous systems, Gidel helps customers push the boundaries of real-time imaging and edge computing. - Published: 2022-07-10 - Modified: 2025-12-09 - URL: https://gidel.com/privacy-policy/ Privacy Policy Last Updated On: 28-Nov-2025Effective Date: 28-Nov-2025 This privacy policy describes how Gidel Ltd. collects, uses, and discloses your information when you visit or interact with Gidel. com. By using the Service, you agree to the practices outlined here. If you do not agree, please stop using the Service. We may update this Privacy Policy without prior notice. Updates become effective 180 days after posting. 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If you choose not to provide required information, or withdraw consent, you may not be able to access certain services. Cookies For details on how we use cookies and tracking technologies, please refer to our Cookie Policy below. Security We use reasonable technical measures to protect your information. Despite this, no method of transmission or storage is fully secure. You provide information at your own risk. Links to Third-Party Sites Our Service may contain links to external websites. We are not responsible for their content, policies, or practices. We recommend reviewing their privacy policies. Grievance / Data Protection Officer If you have concerns about how your information is handled, you may contact our Grievance Officer: Gidel Ltd. 12 Ha’ilan St. , Northern Industrial Zone, P. O. Box 281Email: support@gidel. com We will address your concerns in accordance with applicable law. Cookie Policy Effective Date: 28-Nov-2025Last Updated: 28-Nov-2025 What Are Cookies? This Cookie Policy explains what cookies are, how we use them, the types of cookies we use, the information we collect through cookies, how that information is used, and how you can manage your cookie settings. Cookies are small text files stored on your device when a website loads in your browser. They help the website function properly, improve security, enhance user experience, and provide performance insights so we can understand what works well and what needs improvement. How We Use Cookies Like most online services, our website uses both first-party and third-party cookies. First-party cookies are essential for website functionality. They do not collect personally identifiable information. Third-party cookies help us understand how the website performs, how users interact with specific pages, keep our services secure, deliver relevant advertisements, and improve the overall user experience. These cookies also help speed up future visits to our website. Types of Cookies We Use We use several categories of cookies, including essential cookies, performance cookies, functional cookies, and advertising cookies. Each category supports a different part of your browsing experience and system performance. (If you want, I can generate a detailed cookie table that matches your actual setup. ) Manage Cookie Preferences You can change your cookie preferences anytime by clicking the Cookie Settings button on this page. This will reopen the cookie consent banner, where you can update your choices or withdraw your consent. Managing Cookies Through Your Browser Most browsers allow you to block or delete cookies. You can modify your browser settings to manage cookies directly. Below are links to support pages for major browsers: Chrome: https://support. google. com/accounts/answer/32050 Safari: https://support. apple. com/en-in/guide/safari/sfri11471/mac Firefox: https://support. mozilla. org/en-US/kb/clear-cookies-and-site-data-firefox Internet Explorer: https://support. microsoft. com/en-us/topic/how-to-delete-cookie-files-in-internet-explorer-bca9446f-d873-78de-77ba-d42645fa52fc If you use another browser, please refer to its official support documentation. ## Posts - Published: 2026-09-04 - Modified: 2026-09-09 - URL: https://gidel.com/vision-2026-gidel-aerospace-defence-innovation/ - Categories: Events, Company Updates - Tags: Embedded Vision, UAV, Defense, Aerospace, FPGA Processing, Image Acquisition, ISR, Recording & Streaming, CoaXPress Frame Grabbers, Edge AI, GigE Vision Frame Grabbers, Camera Link Frame Grabbers, FPGA Compression, VISION Show 2026 Gidel’s FantoVision Mini Edge AI & FPGA Systems have been selected as a VISION Guided Tours Innovation in Aerospace & Defence. Discover real-time multi-sensor acquisition, deterministic FPGA processing, Quality+ Compression, and NVIDIA Jetson AI for tracking, detection, and classification. Gidel at VISION 2026: FantoVision for Aerospace & Defence Gidel will exhibit at VISION 2026 in Stuttgart, Germany, 6–8 October, showcasing FantoVision and its latest FPGA-based imaging and Edge AI technologies for Aerospace & Defence applications. In addition, VISION has selected our innovation, FantoVision: Mini Edge AI & FPGA Systems, as a VISION Guided Tours Innovation in Aerospace & Defence. FantoVision combines multi-sensor acquisition, deterministic FPGA preprocessing, real-time image enhancement, Quality+ Compression, and NVIDIA Jetson AI. As a result, it enables real-time tracking, detection, and classification. Real-Time FPGA Imaging and Edge AI FantoVision is designed for demanding imaging applications that require high bandwidth, low latency, deterministic processing, and AI close to the sensors. First, the FPGA processes image data directly and performs real-time preprocessing, enhancement, and compression. Then, FantoVision transfers the optimized image data to NVIDIA Jetson for AI processing. Consequently, this architecture reduces CPU and GPU imaging workload while maintaining predictable real-time performance. Key capabilities include: Multi-sensor acquisition with CoaXPress-12, GigE Vision, and Camera Link Deterministic FPGA preprocessing with low latency Real-time image processing and enhancement Quality+ Compression for reducing image bandwidth and storage requirements NVIDIA Jetson AI for tracking, detection, and classification Multi-camera acquisition, synchronization, and processing Compact, low-SWaP architecture for embedded and mobile imaging systems Imaging for Aerospace & Defence Applications Aerospace and defence imaging systems increasingly need to acquire, process, compress, and analyze high-resolution sensor data directly at the edge. At the same time, these systems must minimize latency, size, weight, and power consumption. FantoVision supports direct acquisition from high-bandwidth CoaXPress cameras and Camera Link cameras, as well as GigE Vision cameras, enabling flexible integration with a wide range of imaging sensors. Therefore, FantoVision integrates image acquisition, FPGA processing, compression, and NVIDIA Jetson AI into one compact system, making it suitable for applications including: EO/IR imaging systems ISR and surveillance Airborne and UAV imaging payloads Target detection, tracking, and classification Multi-camera and multi-sensor systems Aerial imaging and inspection Armored vehicle vision systems Real-time recording and streaming VISION Guided Tours Innovation in Aerospace & Defence The VISION Guided Tours give visitors a concentrated overview of relevant machine vision innovations for specific application areas. For the Aerospace & Defence category, VISION selected FantoVision as a VISION Guided Tours Innovation. In particular, FantoVision addresses systems that require compact architecture, high-bandwidth image acquisition, deterministic FPGA processing, real-time compression, and Edge AI. See Gidel’s FantoVision at VISION 2026 Visit Gidel at VISION 2026 to see FantoVision in action and discuss your Aerospace & Defence imaging application with our experts. During the show, our live demonstration will combine multi-sensor CoaXPress-12 image acquisition, deterministic FPGA processing, Quality+ Compression, and NVIDIA Jetson AI. Together, these technologies enable real-time detection, tracking, and classification. See FantoVision in Action: Real-Time C-UAS Detection & Classification Download the FantoVision Datasheet Find us at Hall 8, Booth 8D20 6–8 October 2026 Messe Stuttgart, Germany VISION Guided Tour: Aerospace & Defence - Published: 2026-08-27 - Modified: 2026-09-09 - URL: https://gidel.com/vision-show-2026-gidel/ - Categories: Events - Tags: Embedded Vision, High-Resolution Imaging, Machine Vision, FPGA Processing, Image Acquisition, CoaXPress Frame Grabbers, Edge AI, GigE Vision Frame Grabbers, Camera Link Frame Grabbers, FPGA Compression, VISION Show 2026, High-Speed Imaging Meet Gidel at VISION Show 2026 and explore FPGA imaging solutions for real-time acquisition, image processing, compression, and Edge AI. See FantoVision process multi-sensor CoaXPress-12 data with NVIDIA Jetson and explore Gidel frame grabbers for CoaXPress, GigE Vision, and Camera Link. VISION Show 2026: Gidel Demonstrates Real-Time FPGA Imaging and Edge AI At VISION Show 2026, Gidel will demonstrate how FPGA-based imaging platforms combine high-bandwidth camera acquisition, deterministic real-time processing, compression, and NVIDIA Jetson Edge AI in compact machine vision systems. Visitors can explore Gidel solutions for CoaXPress, GigE Vision, and Camera Link cameras, ranging from high-performance PCIe FPGA frame grabbers to complete embedded NVIDIA Jetson + FPGA vision systems. FantoVision40-CXP12: Real-Time Embedded Imaging and Edge AI FantoVision40-CXP12: Mini Edge AI System with FPGA The live demonstration will show a complete embedded AI vision pipeline combining Gidel FPGA technology with NVIDIA Jetson Orin NX. The FPGA handles deterministic acquisition from multiple sensors, performs real-time preprocessing, and applies Gidel’s proprietary Quality+ Compression before transferring image data to the Jetson for AI workloads such as detection, tracking, and classification. The system simultaneously acquires images from two CoaXPress-12 cameras, one IR and one RGB Bayer, processing 13MP images at 30 FPS while maintaining high image quality. This heterogeneous FPGA + Jetson architecture reduces CPU/GPU workload, lowers system latency, and leaves more Jetson computing resources available for AI application processing. Engineers evaluating high-bandwidth camera configurations can also review Gidel’s guide to CoaXPress cameras for bandwidth, link count, cabling, synchronization, and acquisition considerations. SkyBoost: High-Resolution FPGA Post-Processing Acceleration SkyBoost: High-Resolution RAW-to-JPEG Imaging Acceleration Gidel will also demonstrate SkyBoost, its FPGA-based image-processing accelerator for very large images, including image sizes above 100MP. SkyBoost uses a PCIe FPGA accelerator installed in the host PC, with image processing running directly on the FPGA. This offloads the main imaging workload from the host CPU or GPU and accelerates high-resolution post-processing. In the live demonstration, SkyBoost will reduce processing time from 30 seconds or more per image to more than two images per second. This can significantly shorten high-resolution imaging workflows that otherwise require hours or, in some cases, days. The technology supports demanding applications including industrial inspection, defense, intelligence, aerial imaging, scientific imaging, and other high-resolution vision systems. For real-time image processing during acquisition, Gidel also provides SkyBoost-RT. FPGA Frame Grabbers for CoaXPress, GigE Vision, and Camera Link Gidel will also present FPGA-based acquisition platforms for demanding machine vision and imaging systems. Gidel PCIe frame grabbers combine high-bandwidth camera acquisition with programmable FPGA resources for optional real-time image processing, image enhancement, compression, data reduction, and application-specific processing. Solutions include CoaXPress frame grabbers, GigE Vision frame grabbers, and the Camera Link frame grabber. FPGA Processing Across the Imaging Workflow Gidel FPGA platforms address different stages of the imaging workflow. A PCIe FPGA frame grabber is well suited to systems where image acquisition and optional FPGA processing operate inside a host workstation or server. FantoVision Mini Edge AI systems provide a different architecture by combining camera acquisition, FPGA processing, and NVIDIA Jetson CPU/GPU computing in a compact standalone system. Both architectures support applications where bandwidth, latency, deterministic processing, and efficient use of CPU/GPU resources are critical. Applications for FPGA Imaging and Edge AI Gidel technologies support high-performance vision systems across industrial, scientific, aerospace, defense, and advanced embedded imaging applications. Industrial inspection and AOI High-speed machine vision Multi-camera imaging systems Robotics and autonomous systems Aerospace and defense imaging Scientific imaging Aerial imaging and ISR High-resolution image processing Embedded Edge AI vision Meet Us at VISION Show 2026 Meet our expert team and see how FPGA acceleration can improve real-time image acquisition, processing, compression, and Edge AI performance. Whether you are developing a high-bandwidth machine vision system, a multi-camera platform, or a compact embedded AI solution, visit Gidel to discuss how FPGA technology can offload demanding imaging workloads from the CPU and GPU while improving determinism and overall system performance. VISION Show 2026 Event Details October 6–8, 2026 Messe Stuttgart, Germany Hall 8, Booth 8D20 Event link: VISION Show 2026 - Published: 2026-08-25 - Modified: 2026-09-07 - URL: https://gidel.com/camera-link-cameras/ - Categories: Technical Articles - Tags: Image Processing, High-Resolution Imaging, Machine Vision, Image Acquisition, Multi-Camera Synchronization, Edge AI, Image Signal Processing, Line-Scan Imaging, Camera Link Cameras, Camera Link Frame Grabbers Selecting the right Camera Link camera involves more than resolution and frame rate. Learn about Base, Medium, Full, and 80-bit Deca configurations, synchronization, acquisition architecture, and FPGA processing for high-speed imaging systems. High-Speed Camera Link Cameras Camera Link cameras are designed for deterministic, low-latency image acquisition using a dedicated point-to-point camera interface. The standard combines high-speed image transfer, camera control, timing, serial communication, and real-time signaling between the camera and frame grabber. This makes Camera Link suitable for industrial inspection, scientific imaging, medical systems, defense, line-scan imaging, high-speed recording, and other demanding imaging applications. Camera Link supports several acquisition configurations, including Base, Medium, Full, and 80-bit Deca, with maximum standardized bandwidth reaching 850 MB/s, or approximately 6. 8 Gb/s. Dual Base configurations can also support two Base cameras from compatible acquisition hardware. Selecting the correct Camera Link camera therefore involves more than resolution and frame rate. Engineers must also consider Camera Link configuration, pixel clock, tap format, pixel depth, cable requirements, PoCL support, triggering, synchronization, frame grabber compatibility, and downstream processing capacity. When Is Camera Link the Right Camera Interface? Camera Link is particularly well suited to imaging systems that require deterministic, low-latency point-to-point acquisition with direct frame-grabber connectivity. Base, Medium, Full, and 80-bit Deca configurations support progressively higher image-data rates, with conventional Camera Link reaching up to 850 MB/s. The interface is especially attractive for established Camera Link camera ecosystems, line-scan imaging, precision triggering, and applications where predictable timing is more important than long cable reach or network flexibility. For systems requiring substantially more than 850 MB/s, very long camera distances, or switched multi-camera networking, another camera interface may be more appropriate. Understanding Camera Link Cameras Camera Link is a dedicated digital imaging interface that standardizes communication between cameras and frame grabbers. Unlike network-based camera interfaces, it uses a direct hardware connection designed specifically for deterministic image acquisition. The standard defines image-data transfer together with camera timing, control signals, and serial communication. Camera Link is hosted and maintained by A3, which manages the standard, compliance framework, and registered Camera Link ecosystem. Camera Link remains a well-established imaging standard with interoperable cameras, frame grabbers, and cables from multiple manufacturers. Some manufacturers and technical documentation also use the spelling CameraLink. Supported camera configurations include: Base Medium Full 80-bit Deca Dual Base, when supported by the acquisition architecture Power over Camera Link, or PoCL, also allows compatible cameras to receive power through the Camera Link connection. Mini Camera Link connectors reduce connector size for compact systems. Typical considerations include: Camera resolution and frame rate Base, Medium, Full, or Deca configuration Pixel clock Number of taps Pixel depth and image format Monochrome or color operation Global or rolling shutter External triggering and synchronization PoCL requirements Cable type and length Area-scan or line-scan architecture Frame grabber and host-system bandwidth Current Camera Link camera portfolios include both area-scan and line-scan systems. CL cameras remain relevant where deterministic acquisition, mature hardware integration, and predictable image timing are important. Camera Link Camera Selection Criteria Select the Camera Link camera according to the complete imaging workload, not the interface configuration alone. Resolution and Sensor Format Higher-resolution sensors capture more spatial detail but generate larger image payloads. The lens and optical format must also match the sensor size and required field of view. Global vs. Rolling Shutter Global-shutter cameras expose the complete image simultaneously and are generally preferred for moving objects and precision measurement. Rolling-shutter sensors may offer advantages in resolution, sensitivity, cost, or availability, but motion artifacts must be considered. Frame Rate Higher frame rates directly increase the required acquisition bandwidth. As resolution, frame rate, or pixel depth increases, a camera may require Medium, Full, or Deca operation instead of Base Camera Link. Pixel Depth and Image Format 8-, 10-, 12-, 14-, 16-bit, and other pixel formats affect image quality, dynamic range, and data rate. Camera and frame grabber tap formats must also be compatible with the transmitted image structure. Camera Link Configuration Base, Medium, Full, and 80-bit Deca provide progressively greater data width and bandwidth. The selected frame grabber must support the exact camera configuration and required pixel clock. Tap Configuration Camera Link cameras may transmit multiple pixels simultaneously using different tap arrangements. The frame grabber must correctly interpret the camera's tap geometry and pixel packing. Triggering and Synchronization Applications involving line-scan acquisition, moving objects, metrology, multi-camera imaging, or high-speed inspection often require precise trigger timing and deterministic acquisition. Acquisition and Processing Architecture The camera is only one part of the data path. The frame grabber, FPGA, PCIe interface, host memory, storage subsystem, GPU, and processing pipeline must all sustain the required image-data rate. Systems that prioritize long cable reach, standard Ethernet infrastructure, or switched multi-camera networking may instead evaluate GigE Vision cameras. Evaluating Bandwidth for High-Resolution and High-Speed Imaging High-resolution and high-speed Camera Link cameras can generate substantial continuous image bandwidth, particularly when operating in Full or 80-bit Deca configurations. The required Camera Link configuration should therefore be evaluated against resolution, frame rate, pixel depth, tap format, and camera count. The required acquisition bandwidth can be estimated from four primary factors: Resolution × frame rate × pixel depth × number of cameras = required image-data bandwidth Higher resolution increases the amount of data in every frame. Frame rate and pixel depth increase the required bandwidth further, while multi-camera systems multiply the total acquisition requirement. Camera Link is particularly useful where a predictable hardware data path and deterministic transfer are more important than network flexibility. The complete acquisition architecture must therefore be dimensioned for the sustained image stream rather than only the nominal camera specification. Camera Link Camera Configurations: Base, Medium, Full & Deca Camera Link cameras use several standardized configurations that determine the number of data bits transmitted and the maximum available interface bandwidth. Camera Link Configuration and Maximum Throughput Configuration Data Width Maximum Throughput Base 24-bit 255 MB/s Medium 48-bit 510 MB/s Full 64-bit 680 MB/s 80-bit Deca 80-bit 850 MB/s Swipe horizontally to view all columns → These maximum values assume operation at the upper standardized Camera Link clock rate. Base Camera Link Cameras Base Camera Link uses a 24-bit data path and is appropriate for moderate-resolution and moderate-frame-rate applications. It also uses fewer physical resources than the higher configurations. Medium Camera Link Cameras Medium expands the data path to 48 bits, providing additional bandwidth for cameras that exceed Base performance. Full Camera Link Cameras Full Camera Link increases the data width to 64 bits and supports higher image throughput for demanding area-scan and line-scan systems. 80-bit Deca Camera Link Cameras 80-bit Deca extends Camera Link to its maximum standardized parallel data width, supporting up to 850 MB/s. It is suited to high-speed cameras requiring the highest throughput available within conventional Camera Link. Dual Base Configurations Compatible frame grabbers may also support two independent Base Camera Link cameras simultaneously. This can provide a compact acquisition architecture for synchronized dual-camera systems. Camera Link Selection by System Requirement Camera Link System Design Guide Requirement Typical Camera Link Direction Moderate image-data bandwidth Base Camera Link More bandwidth than Base Medium Camera Link High-resolution or high-frame-rate imaging Full Camera Link Maximum conventional Camera Link throughput 80-bit Deca Two independent Base cameras Dual Base Deterministic point-to-point acquisition Camera Link with dedicated frame grabber Compact camera connector Mini Camera Link / SDR-26 Camera power through acquisition cable PoCL-capable camera and frame grabber Short, direct camera-to-frame-grabber connection Conventional Camera Link cabling Reduced host processing or data volume FPGA preprocessing in acquisition path Swipe horizontally to view all columns → Choosing the Right Camera Link Connectivity and Cabling Camera Link uses a dedicated point-to-point cable connection between the camera and frame grabber. Dedicated Camera Connection Each Camera Link camera connects directly to compatible acquisition hardware. This avoids shared network bandwidth and simplifies deterministic image transfer. Cable Length The original Camera Link specification was designed around cable lengths of up to approximately 10 m. Actual supported distance can depend on the camera, pixel clock, cable quality, and acquisition hardware, while specialized extenders can support longer installations. Mini Camera Link Mini Camera Link uses the smaller SDR-26 connector format for compact cameras and acquisition hardware, while conventional Camera Link systems commonly use MDR-26 connectors. The smaller connector footprint preserves Camera Link functionality while helping simplify integration in space-constrained imaging systems. Power over Camera Link PoCL allows compatible cameras to receive power from the frame grabber through the Camera Link cable. This can reduce separate camera-power wiring and simplify installation. Camera Link Limits and Design Considerations Camera Link provides deterministic acquisition and a mature hardware ecosystem, but several design constraints should be considered. Dedicated Frame Grabber Requirement A Camera Link camera normally requires a compatible frame grabber. The camera cannot simply connect to a standard host network or USB interface. Configuration Compatibility The frame grabber must support the camera's Base, Medium, Full, Deca, or Dual Base configuration together with the required tap format and pixel clock. Cable Reach Camera Link is optimized for direct camera-to-frame-grabber connectivity rather than very long distributed links. Longer distances may require specialized cables or extenders. Physical Cabling Higher Camera Link configurations can require two Camera Link connections, increasing connector and cable requirements compared with Base operation. Bandwidth Ceiling Conventional Camera Link reaches a maximum standardized throughput of 850 MB/s. Applications requiring substantially higher point-to-point camera bandwidth may evaluate CoaXPress cameras as an alternative architecture. Camera Link HS is a separate standard and should not be confused with conventional Camera Link. Example Applications High-Speed Industrial Inspection Camera Link cameras are well suited to inspection systems that require predictable acquisition timing, external triggering, and reliable image transfer. High-Resolution Imaging Full and Deca Camera Link cameras can support high-resolution image acquisition in scientific, medical, electronics, semiconductor, and other demanding imaging applications. Line-Scan Imaging Camera Link has long been used for line-scan applications where continuous data flow and precise timing are critical. Typical applications include web inspection, sorting, printing, surface inspection, and materials analysis. Metrology and Precision Imaging Deterministic triggering and direct frame-grabber connectivity make Camera Link useful in measurement systems where acquisition timing must be tightly controlled. Multi-Camera Vision Dual Base and scalable multi-frame-grabber architectures can support synchronized camera configurations for multi-view imaging, inspection, and sensor arrays. Defense, Aerospace and Scientific Imaging The mature ecosystem, deterministic acquisition path, and availability of high-resolution Camera Link cameras make the interface relevant to specialized imaging systems with long product lifecycles. Edge AI and Real-Time Analytics FPGA preprocessing, ROI selection, Compression, Detection, and image enhancement can reduce the amount of raw Camera Link data that must be processed later by a host CPU, GPU, or embedded AI processor. Modern Camera Link Camera Vendors & Configurations Camera Link remains available across area-scan, line-scan, high-resolution, color, multispectral, and specialized scientific camera families. JAI supports Camera Link across both area-scan and line-scan products. Current examples include Mini Camera Link area-scan cameras as well as 16K line-scan configurations. Basler has supplied Camera Link cameras for industrial imaging, including its ace Camera Link family in Base and higher-performance configurations. Camera Link products remain represented in the A3 compliant-product ecosystem. Teledyne Vision Solutions supports Camera Link across high-performance imaging ecosystems, including line-scan and specialized imaging applications where deterministic acquisition and frame-grabber integration remain important. Hamamatsu Photonics offers high-sensitivity Camera Link scientific cameras, including the ORCA-Quest IQ qCMOS camera. Its Camera Link output supports applications such as quantum technology, adaptive optics, and super-resolution microscopy, where low-noise acquisition and high-speed feedback to external control systems are important. illunis develops high-resolution Camera Link cameras for demanding imaging applications. Its portfolio includes large-format area-scan models designed for industrial, scientific, aerial, defense, and other high-resolution imaging systems. illunis High-Resolution Camera Link Cameras The important system-design question is therefore not simply whether a camera uses Camera Link, but which configuration it requires, what pixel clock and tap format it uses, and how much sustained data the complete acquisition and processing pipeline must handle. Camera Link Acquisition Platforms and FPGA Processing Once the camera requirements are defined, the next step is selecting an acquisition and processing architecture that supports the required Camera Link configuration, pixel clock, triggering, synchronization, and real-time image-processing needs. Gidel provides PCIe Camera Link frame grabbers and compact Edge AI systems supporting Base, Medium, Full, 80-bit Deca, and Dual Base acquisition, with optional PoCL and inline FPGA processing. PCIe Frame Grabbers for Camera Link Cameras High-speed Camera Link cameras require acquisition hardware that matches the camera configuration, tap format, synchronization requirements, and sustained image-data rate. A Camera Link frame grabber receives image data directly from the camera, handles timing and acquisition, buffers the image stream where required, and transfers data into the host computer through PCIe. Gidel's HawkEye-CL supports: 1 × 80-bit Deca Camera Link camera 1 × Full Camera Link camera 1 × Medium Camera Link camera 1 × Base Camera Link camera Dual Base operation Optional PoCL The HawkEye-CL supports Camera Link acquisition up to 6. 8 Gb/s together with optional inline FPGA image processing and up to 17 GB of onboard memory. Gidel's Camera Link frame-grabber architecture supports deterministic acquisition together with FPGA-based processing directly in the image path. Edge AI Systems with Camera Link Frame Grabbers Applications that benefit from a compact embedded architecture can use an integrated Edge AI system instead of a conventional host computer with a PCIe frame grabber. Gidel's FantoVision20-CL combines an NVIDIA Jetson processor, Altera FPGA, and integrated Camera Link acquisition in a compact system. It supports Deca, Full, Medium, Base, and Dual Base configurations with acquisition bandwidth up to 6. 8 Gb/s. The system combines FPGA-based camera acquisition and preprocessing with NVIDIA Jetson CPU/GPU computing for AI inference, application processing, recording, and streaming. Gidel FantoVision20-CL Mini Edge AI System This creates two distinct architecture options: Gidel PCIe Camera Link frame grabber:Installed in a host computer and provides Camera Link acquisition, optional FPGA processing, and high-speed PCIe transfer for host-side processing, storage, and application execution. Gidel Mini Edge AI system with Camera Link frame grabber:A complete compact embedded vision system integrating Camera Link acquisition, FPGA processing, and NVIDIA Jetson CPU/GPU computing in one platform. For applications requiring both GigE Vision and Camera Link cameras, the FantoVision20 combines Dual 10 GigE Vision and Camera Link acquisition support. Real-Time FPGA Image Processing for Camera Link Acquisition High-speed Camera Link cameras can generate more image data than the host application needs in raw form. Gidel FPGA-based acquisition platforms can optionally process data while it is being acquired. Available functions include Compression, Detection, ROI/data reduction, HDR correction, custom FPGA processing, and other real-time image-processing operations. Processing data directly in the acquisition path can help: Reduce host bandwidth and storage requirements Lower host CPU/GPU load Preserve low-latency operation Execute deterministic processing Reduce data volume before recording, streaming, or AI inference This is particularly useful in high-resolution, line-scan, and high-frame-rate Camera Link systems where deterministic processing must operate continuously with acquisition. ISP and Image Enhancement High-resolution Camera Link cameras may require dedicated ISP and image-enhancement functions before display, recording, analysis, or AI inference. When the camera does not already implement these functions, the FPGA acquisition path can execute them before data reaches the host CPU or GPU. Depending on the sensor and application, processing may include debayering, white balance, gain and offset correction, HDR correction, bad-pixel correction, non-uniformity correction, dynamic luminance balancing, and color or luminance optimization. Gidel acquisition platforms can integrate selected ISP and image-processing functions directly into the FPGA path using existing Gidel capabilities, customer-developed IP, or application-specific algorithms. Inline ISP processing can reduce host CPU/GPU load, preserve low latency, and prepare image data earlier for recording, streaming, visualization, analysis, or AI processing. Building Your Own ISP with Gidel Platforms Gidel platforms provide several ways to build and customize an FPGA-based ISP pipeline. Customers can use Gidel's off-the-shelf image-processing algorithms, integrate their own FPGA algorithms, develop new processing functions using Gidel's ProcVision Suite, or work with Gidel to develop application-specific algorithms. These approaches can also be combined within the same pipeline, allowing existing Gidel functions, customer-developed IP, and newly developed algorithms to operate together directly in the FPGA acquisition path. Using ProcVision Suite, experienced FPGA developers can implement application-specific stages such as debayering, gain and offset correction, HDR, image enhancement, ROI handling, Detection, Compression, and other custom processing functions. This flexibility allows the pipeline to be tailored to the camera, sensor, and application while executing deterministically before data reaches the host CPU, GPU, or Jetson processor. Multi-Camera Synchronization and Scalable Acquisition Multi-camera Camera Link systems require more than sufficient aggregate bandwidth. Frames must also be acquired with deterministic timing and controlled synchronization. Gidel's InfiniVision architecture is designed for scalable synchronized acquisition across multiple cameras and acquisition systems. Configurations can scale to 100+ synchronized Camera Link cameras while retaining FPGA-based data handling. This architecture is relevant to applications such as: Synchronized multi-view imaging Volumetric imaging 3D vision Line-scan arrays Large inspection systems Defense and scientific imaging Distributed acquisition systems Camera Link Camera Alternative for Development and Validation During early-stage development, system integration, and validation, engineers may not always have access to the final Camera Link camera or may need repeatable image streams that are difficult to reproduce with a physical camera. A Camera Link simulator can generate controlled video streams and test patterns, allowing frame grabbers, processing pipelines, triggering, and system behavior to be validated under repeatable conditions. Gidel's CamSim-CL is a Camera Link camera simulator supporting Base, Medium, Full, and 80-bit Deca configurations. It can generate programmable Camera Link image streams and provides a practical alternative to physical Camera Link cameras during development and validation. So, Which Camera Link Camera Is Right for You? There is no single “best” Camera Link camera for every application. The right choice depends on sensor requirements, Camera Link configuration, frame rate, pixel depth, triggering, synchronization, and downstream processing capacity. Moderate-Bandwidth Imaging:Base Camera Link can be a practical choice where the required image stream fits within the available bandwidth and system simplicity is important. Higher-Resolution and Higher-Frame-Rate Imaging:Medium and Full Camera Link provide additional bandwidth for cameras that exceed Base performance. Maximum Camera Link Throughput:80-bit Deca supports the highest standardized conventional Camera Link bandwidth, up to 850 MB/s, for demanding area-scan and line-scan applications. Dual-Camera Systems:Dual Base configurations can support two Base cameras from compatible acquisition hardware while retaining direct deterministic connectivity. Line-Scan and Precision Imaging:Prioritize camera and frame-grabber compatibility, tap configuration, triggering, and deterministic timing. These factors are often as important as the nominal interface bandwidth. Compact and Embedded Deployments:Camera Link cameras can be paired with Edge AI platforms combining FPGA-based acquisition with NVIDIA Jetson CPU/GPU processing. High-Throughput and Data-Intensive Pipelines:Inline FPGA processing for Compression, ISP, HDR, Detection, or data reduction can reduce host bandwidth, storage requirements, and CPU/GPU load. Need help configuring your Camera Link acquisition and processing pipeline? Explore Gidel's PCIe Camera Link frame grabber. Gidel PCIe Camera Link Frame Grabber Need help selecting the right acquisition, FPGA processing, and synchronization architecture for your Camera Link camera system? Contact Us. - Published: 2026-08-25 - Modified: 2026-09-07 - URL: https://gidel.com/gige-vision-cameras/ - Categories: Technical Articles - Tags: Image Processing, High-Resolution Imaging, Machine Vision, Image Acquisition, Multi-Camera Synchronization, Edge AI, Image Signal Processing, GigE Vision Cameras, 10 GigE Vision, GigE Vision Frame Grabbers, GigE Cameras, Line-Scan Imaging Selecting the right GigE Vision camera involves more than resolution and frame rate. Learn about 1, 2.5, 5, and 10 GigE Vision, network connectivity, synchronization, acquisition architecture, and FPGA processing for high-speed imaging systems. High-Speed GigE Vision Cameras GigE Vision cameras are designed for flexible, high-performance image acquisition using standard Ethernet technology. They combine image transmission, camera control, triggering, and standardized camera configuration over an Ethernet connection, making them well suited for machine vision, scientific imaging, medical imaging, robotics, inspection, defense, distributed imaging, and multi-camera applications. Modern GigE cameras are available across several Ethernet speeds, including 1, 2. 5, 5, and 10 GigE Vision. Higher interface speeds provide additional bandwidth for increased resolution, frame rate, pixel depth, or multiple simultaneous camera streams. Selecting the correct GigE Vision camera therefore involves more than resolution and frame rate. Engineers must also consider Ethernet speed, network architecture, camera count, cable type and distance, PoE requirements, synchronization, packet handling, acquisition bandwidth, host connectivity, and downstream image-processing requirements. When Is GigE Vision the Right Camera Interface? GigE Vision is particularly well suited to imaging systems that require long cable reach, flexible camera placement, standard Ethernet infrastructure, and scalable multi-camera networking. 1 GigE Vision fits moderate-bandwidth applications, while 2. 5, 5, and 10 GigE Vision provide progressively higher throughput for increased resolution and frame rate. GigE Vision is especially attractive when cameras must operate over long copper or fiber connections, share switched network infrastructure, or use PoE and PTP-based synchronization. For very high-bandwidth systems, however, aggregate network capacity, packet handling, buffering, and host throughput must be engineered carefully. Understanding GigE Cameras GigE Vision is a standardized machine vision interface built on Ethernet technology. It allows image data and camera-control traffic to be transported over familiar Ethernet infrastructure while providing standardized device discovery, configuration, and image streaming. GigE Vision is hosted and maintained by A3, which manages the standard and its ongoing development. This helps maintain interoperability across GigE Vision cameras, acquisition hardware, software, and network-based imaging systems. A major advantage of GigE Vision is its use of standard networking technology. Depending on the camera and system architecture, GigE Vision cameras can use copper or fiber connections, Ethernet switches, conventional network infrastructure, and standard physical-layer technologies. Standard copper Ethernet can support cable runs of approximately 100 meters, substantially simplifying installations where cameras must be located far from the acquisition system. Fiber connections can extend camera placement even farther while also providing electrical isolation. GigE Vision cameras may operate at different Ethernet speeds, including: 1 GigE Vision cameras 2. 5 GigE Vision cameras 5 GigE Vision cameras 10 GigE Vision cameras Typical considerations include: Camera resolution and frame rate GigE Vision interface speed Number of cameras Monochrome or color operation Pixel depth Global or rolling shutter External triggering and synchronization PTP support PoE requirements Cable type and distance Copper or fiber connectivity Network topology and switching Area-scan or line-scan architecture Frame grabber, network, and host-system bandwidth Current GigE Vision camera portfolios include both area-scan and line-scan models, ranging from compact 1 GigE industrial cameras to high-resolution and high-frame-rate 5 GigE and 10 GigE Vision cameras. GigE Vision Camera Selection Criteria The correct GigE Vision camera should be selected according to the complete imaging workload, not Ethernet speed alone. Resolution and Sensor Format Higher-resolution sensors capture more spatial detail but also generate larger image payloads. The optical format and lens must match the sensor size and required field of view. Global vs. Rolling Shutter Global-shutter cameras expose the complete image simultaneously and are generally preferred for fast-moving objects and precision measurement. Rolling-shutter sensors may offer advantages in resolution, sensitivity, cost, or availability, but motion artifacts must be considered. Frame Rate Higher frame rates directly increase the required bandwidth. As resolution, frame rate, or pixel depth increases, a camera may need 2. 5, 5, or 10 GigE Vision instead of 1 GigE. Pixel Depth and Image Format 8-, 10-, 12-, or higher-bit formats affect image quality, dynamic range, and data rate. Color transmission can also increase the required bandwidth. Ethernet Speed 1 GigE Vision may be sufficient for moderate image streams. 2. 5 and 5 GigE Vision provide intermediate bandwidth levels, while 10 GigE Vision supports substantially higher data rates. Network Architecture GigE Vision cameras can connect directly to acquisition hardware or through Ethernet switches. Multi-camera systems must provide sufficient switch, uplink, buffering, and acquisition bandwidth. Triggering and Synchronization Multi-camera, metrology, 3D, robotics, and line-scan applications may require precise synchronization. GigE Vision systems can use hardware triggering and network-based clock synchronization. Acquisition and Processing Architecture The Ethernet interface, switch, FPGA, PCIe path, host memory, storage, GPU, and processing pipeline must all support the sustained image-data rate. Systems built around existing Camera Link cameras may instead use a direct frame-grabber architecture without Ethernet networking. Evaluating Bandwidth for High-Resolution and High-Speed Imaging High-resolution and high-speed GigE Vision cameras can generate image streams that exceed the practical bandwidth of conventional 1 GigE acquisition. The required Ethernet speed should therefore be evaluated against resolution, frame rate, pixel depth, and camera count. The required acquisition bandwidth can be estimated from four primary factors: Resolution × frame rate × pixel depth × number of cameras = required image-data bandwidth Higher resolution increases the data in each frame, while higher frame rates and pixel depths further increase the required bandwidth. Multi-camera systems multiply those requirements again. Modern GigE cameras therefore range from compact 1 GigE systems to 2. 5, 5, and 10 GigE Vision cameras for higher-resolution and higher-frame-rate imaging. The acquisition interface, network infrastructure, PCIe path, and downstream processing system must sustain the resulting data flow without packet loss or host-side bottlenecks. 1, 2. 5, 5 and 10 GigE Vision Cameras GigE Vision benefits from the scalability of Ethernet, allowing the interface speed to be matched to the required image-data bandwidth. GigE Vision Ethernet Speed and Maximum Link Rate Configuration Maximum Ethernet Link Rate 1 GigE Vision 1 Gb/s 2. 5 GigE Vision 2. 5 Gb/s 5 GigE Vision 5 Gb/s 10 GigE Vision 10 Gb/s Swipe horizontally to view all columns → The usable image-data throughput is lower than the nominal Ethernet rate because protocol overhead must also be transmitted. 1 GigE Vision Cameras1 GigE Vision remains well suited to applications where moderate bandwidth, standard Ethernet infrastructure, long cable reach, and cost efficiency are more important than maximum throughput. 2. 5 GigE Vision Cameras2. 5 GigE Vision provides additional bandwidth when 1 GigE is no longer sufficient without requiring a 5 or 10 GigE architecture. 5 GigE Vision Cameras5 GigE Vision supports higher resolutions and frame rates while retaining the flexibility of Ethernet-based acquisition. 10 GigE Vision Cameras10 GigE Vision is suited to high-resolution, high-frame-rate, and data-intensive imaging. Depending on the camera and acquisition hardware, connections may use copper or fiber. Gidel's GigE Vision frame-grabber family supports optional inline FPGA processing directly in the acquisition path across multiple Ethernet speeds and camera-count configurations. GigE Vision Selection by System Requirement GigE Vision System Design Guide Requirement Typical GigE Vision Direction Moderate bandwidth, lowest infrastructure complexity 1 GigE Vision More bandwidth without moving directly to 5/10 GigE 2. 5 GigE Vision Higher resolution or frame rate with Ethernet flexibility 5 GigE Vision High-throughput area-scan or line-scan imaging 10 GigE Vision Long copper connection Up to approximately 100 m Longer reach or electrical isolation Fiber connectivity Multiple distributed cameras Switched Ethernet architecture Single-cable power and data PoE-capable camera/system Network-based clock synchronization PTP-capable camera and infrastructure Reduced host processing or data volume FPGA preprocessing in acquisition path Swipe horizontally to view all columns → Choosing the Right Connectivity and Network Architecture One of the major advantages of GigE Vision is its use of established Ethernet infrastructure. Depending on the camera and installation, systems can use standard Ethernet cabling, copper or fiber connections, Ethernet switches, PoE, and distributed multi-camera network topologies. Long Cable Reach Copper Ethernet links can reach approximately 100 m, while fiber can extend camera placement significantly farther and provide electrical isolation or improved EMI immunity. Physical Connectors GigE Vision cameras commonly use RJ45 Ethernet connectors for copper connections, while industrial implementations may use ruggedized M12 connectors. Higher-speed systems can also use fiber interfaces such as SFP+ for 10 GigE Vision, depending on the camera and acquisition architecture. Flexible Multi-Camera Networking Ethernet switches allow multiple GigE Vision cameras to share network infrastructure rather than requiring every camera to connect directly to the acquisition system. Switch capacity and uplink bandwidth must be sized for the combined camera traffic. Power over Ethernet Compatible cameras can combine power and data on a single Ethernet cable using PoE, reducing installation and cabling complexity. PTP-Based Synchronization Compatible GigE Vision cameras and acquisition devices can use Precision Time Protocol to synchronize clocks across the network. Hardware triggering can also be used where precise acquisition timing is required. Scalability Beyond 10 GigE The Ethernet foundation also gives GigE Vision a clear technology path toward much higher bandwidths. GigE Vision 3. 0 was approved in April 2026 and introduces RoCEv2-based streaming for significantly higher Ethernet throughput and reduced host involvement. GigE Vision Network Limits and Design Considerations Ethernet provides substantial flexibility, but high-performance GigE Vision systems must be designed around the complete network and acquisition path. Protocol Overhead and Packet Handling The nominal Ethernet link rate is higher than the usable image-data throughput because network and GigE Vision protocols consume part of the available bandwidth. The acquisition interface, buffers, drivers, and software must also sustain the incoming packet rate without loss. Shared Network Bandwidth When multiple cameras share a switch or uplink, their combined image-data rate must remain within the available network bandwidth. Buffering and Network Configuration High-bandwidth systems may require suitable buffering, packet sizing, switch configuration, NIC settings, and host tuning to avoid packet loss or incomplete frames. Timing and Synchronization Ethernet image transport should not be assumed to be inherently deterministic. Applications requiring precise acquisition timing should use hardware triggering, timestamping, PTP synchronization, or dedicated acquisition hardware as appropriate. Applications that prioritize very high deterministic point-to-point camera bandwidth may also evaluate CoaXPress cameras as an alternative acquisition architecture. Example Applications Industrial Inspection GigE Vision cameras are widely used in inspection systems where standard networking, flexible camera placement, and scalable acquisition are important. High-Resolution Imaging 5 GigE and 10 GigE Vision cameras provide additional bandwidth for higher-resolution sensors and increased frame rates in semiconductor, electronics, medical, and scientific imaging. Line-Scan Imaging High-speed GigE Vision line-scan cameras are well suited to web inspection, sorting, printing, surface inspection, and other continuous imaging applications. Multi-Camera Vision Ethernet switching allows multiple cameras to share network infrastructure while appropriate synchronization mechanisms coordinate acquisition. Long-Distance and Distributed Imaging Copper links of approximately 100 m and longer fiber connections make GigE Vision particularly useful when cameras are physically separated from the acquisition system. Robotics and Embedded Vision GigE Vision cameras integrate naturally into robotic and embedded systems that already use Ethernet networking. Edge AI and Real-Time Analytics FPGA preprocessing, ROI selection, Compression, Detection, and other data-reduction functions can reduce the amount of high-resolution image data sent to an embedded GPU for AI inference. Modern GigE Vision Camera Vendors & Configurations The current market illustrates the broad use of GigE Vision across industrial, high-resolution, line-scan, multi-camera, and high-speed imaging. Basler covers a broad range of GigE Vision cameras for industrial imaging, with models spanning multiple resolutions, sensor formats, and performance levels. Teledyne Vision Solutions supports a wide range of GigE camera configurations, from conventional GigE to higher-speed Ethernet interfaces for industrial, scientific, and other data-intensive imaging applications. LUCID Vision Labs focuses on GigE Vision cameras across several Ethernet bandwidth levels, including high-speed configurations for demanding machine vision and imaging systems. Hamamatsu Photonics offers GigE Vision cameras for specialized industrial imaging, including InGaAs SWIR line-scan cameras for real-time in-line inspection, semiconductor wafer inspection, material analysis, and other applications requiring sensitivity beyond the visible spectrum. illunis develops high-resolution 10 GigE Vision cameras for demanding imaging applications, with large-format global-shutter sensors. Its EMC2 camera family is aimed at aerial imaging, embedded systems, industrial inspection, scientific imaging, and other applications that require high-resolution Ethernet-based acquisition. illunis High-Resolution 10 GigE Vision Cameras The important system-design question is therefore not simply whether a camera uses GigE Vision, but what Ethernet speed it requires, how many cameras share the acquisition architecture, and how much sustained image data the complete network and processing pipeline must handle. GigE Vision Acquisition Platforms and FPGA Processing Once the camera requirements are defined, the next step is selecting an acquisition and processing architecture that can support the required Ethernet speed, camera count, aggregate bandwidth, synchronization, network topology, and real-time image-processing needs. Gidel provides PCIe GigE Vision frame grabbers and compact Edge AI systems for GigE camera acquisition, with support for 1, 2. 5, 5, and 10 GigE Vision cameras, optional inline FPGA processing, and scalable multi-camera synchronization. PCIe Frame Grabbers for GigE Vision Cameras High-speed GigE Vision cameras require acquisition hardware that matches the camera's Ethernet speed, camera count, synchronization requirements, and sustained image-data rate. A GigE Vision frame grabber receives image data from the cameras, handles acquisition and buffering, provides synchronization and optional FPGA processing, and transfers image data into the host computer through PCIe. Gidel's PCIe GigE Vision portfolio includes: HawkEye-20GigE: up to 2 × 10 GigE cameras, 4 × 5 GigE cameras, 8 × 2. 5 GigE cameras, or 20 × 1 GigE cameras Proc10A-40GigE: up to 4 × 10 GigE cameras, 8 × 5 GigE cameras, 16 × 2. 5 GigE cameras, or 30 × 1 GigE cameras Proc1C10M-120GigE: Up to 12 × 10 GigE cameras, 4 × 100 GigE cameras Proc1C10N-120GigE: Up to 12 × 10 GigE cameras, 4 × 100 GigE cameras and AI Tensor Blocks These boards support GigE Vision acquisition across multiple Ethernet speeds, with copper and fiber connectivity options depending on the product configuration. Gidel's GigE Vision frame-grabber family supports optional inline FPGA processing directly in the acquisition path across these Ethernet camera configurations. Edge AI Systems with GigE Vision Frame Grabbers Applications that benefit from a compact embedded architecture can use an integrated Edge AI system instead of a conventional host computer with a PCIe frame grabber. Gidel's FantoVision20-GigE combines an NVIDIA Jetson processor, Altera FPGA, and integrated Dual 10 GigE Vision acquisition in a compact system. It supports image acquisition from 2 × 10 GigE Vision streams. The system combines FPGA-based camera acquisition and preprocessing with NVIDIA Jetson CPU/GPU computing for AI inference, application processing, recording, and streaming. Gidel FantoVision20-GigE Mini Edge AI System This creates two distinct architecture options: Gidel PCIe GigE Vision frame grabber:Installed in a host computer and provides GigE Vision camera acquisition, optional FPGA processing, and high-speed data transfer through PCIe to the host system for further processing, storage, and application execution. Gidel Mini Edge AI system with GigE Vision frame grabber:A complete compact embedded vision system that integrates GigE Vision camera acquisition, FPGA processing, and NVIDIA Jetson CPU/GPU computing in one platform. It is designed for applications that benefit from an integrated Edge AI architecture rather than a separate host computer with a PCIe acquisition card. For applications requiring both Camera Link and GigE Vision cameras, the FantoVision20 combines Camera Link and Dual 10 GigE Vision acquisition support. Real-Time FPGA Image Processing for GigE Vision Acquisition High-speed GigE cameras can produce more data than the host application needs in its raw form. Gidel FPGA-based acquisition platforms can optionally process image data as it is acquired, before host-side processing. Available functions include Compression, Detection, ROI/data reduction, custom FPGA processing, and other real-time image-processing operations. Gidel's current GigE Vision frame grabbers list optional FPGA compression and image-processing capabilities directly in the acquisition path. Processing data directly in the acquisition path can help: Reduce host bandwidth and storage requirements Lower host CPU/GPU load Preserve low-latency operation Execute deterministic processing Reduce data volume before recording, streaming, or AI inference This becomes increasingly relevant as GigE Vision systems scale toward 5 and 10 GigE cameras, multiple simultaneous image streams, and high-resolution configurations. ISP and Image Enhancement High-resolution GigE Vision cameras may require dedicated ISP and image-enhancement functions before display, recording, analysis, or AI inference. When these functions are not already implemented inside the camera, they can be executed in the FPGA acquisition path before the image data reaches the host CPU or GPU. Depending on the sensor and application, functions may include debayering, white balance, gain and offset correction, HDR correction, bad-pixel correction, non-uniformity correction, dynamic luminance balancing, and color or luminance optimization. Gidel acquisition platforms can integrate selected ISP and image-processing functions directly into the FPGA acquisition path using existing Gidel capabilities, customer-developed IP, or application-specific algorithms. Inline ISP processing can reduce host CPU/GPU load, preserve low latency, and prepare image data earlier for recording, streaming, visualization, analysis, or AI processing. Building Your Own ISP with Gidel Platforms Gidel platforms provide several ways to build and customize an FPGA-based ISP pipeline. Customers can use Gidel's off-the-shelf image-processing algorithms, integrate their own FPGA algorithms, develop new processing functions using Gidel's ProcVision Suite, or work with Gidel to develop application-specific algorithms. These approaches can also be combined within the same processing pipeline, allowing existing Gidel functions, customer-developed IP, and newly developed algorithms to operate together directly in the FPGA acquisition path. Using ProcVision Suite, experienced FPGA developers can implement and integrate application-specific processing stages such as debayering, gain and offset correction, HDR, image enhancement, ROI handling, Detection, Compression, and other custom processing functions. This flexibility allows the processing pipeline to be tailored to the camera, sensor, and application requirements while executing deterministically in the FPGA before data reaches the host CPU, GPU, or Jetson processor. Multi-Camera Synchronization and Scalable Acquisition Multi-camera GigE Vision systems require more than sufficient aggregate network bandwidth. Frames must also be acquired with controlled timing and synchronization. GigE Vision can support network-based synchronization mechanisms such as IEEE 1588 PTP when implemented by the cameras and network infrastructure, in addition to conventional hardware triggering. Gidel's InfiniVision architecture is designed for scalable synchronized acquisition across multiple cameras and acquisition systems. Configurations can scale to 100+ synchronized cameras across GigE Vision and Gidel's other supported imaging interfaces. This architecture is relevant to applications such as: Synchronized multi-view imaging Volumetric imaging 3D vision High-speed sensor arrays Large inspection systems Defense and scientific imaging Distributed acquisition systems So, Which GigE Vision Camera Is Right for You? There is no single “best” GigE Vision camera for every application. The right choice depends on sensor requirements, Ethernet speed, network architecture, camera count, synchronization, and downstream processing. Standard Industrial Imaging:Consider 1 GigE Vision cameras where moderate bandwidth, long cable reach, standard networking, and cost efficiency are more important than maximum throughput. Higher-Resolution and Higher-Frame-Rate Imaging:2. 5 and 5 GigE Vision cameras provide additional bandwidth when 1 GigE is no longer sufficient, without immediately requiring a 10 GigE architecture. High-Throughput Imaging:10 GigE Vision cameras suit high-resolution, high-frame-rate, and data-intensive area-scan or line-scan applications. The network, PCIe path, and host system must sustain the resulting data rate. Multi-Camera and Distributed Imaging:Prioritize synchronization support, sufficient switch bandwidth, and adequate uplink capacity. Hardware triggering or PTP can coordinate acquisition timing across multiple cameras. Long-Distance Camera Installations:GigE Vision is particularly useful when cameras are located far from the acquisition system. Copper Ethernet can support approximately 100 m, while fiber can extend significantly farther. Compact and Embedded Deployments:GigE Vision cameras can be paired with Edge AI platforms that combine FPGA acquisition with NVIDIA Jetson CPU/GPU processing. High-Throughput and Data-Intensive Pipelines:Inline FPGA processing for Compression, ISP, HDR, Detection, or data reduction can reduce host bandwidth, storage requirements, and CPU/GPU load. Need help configuring your GigE Vision acquisition and processing pipeline? Explore Gidel's PCIe GigE Vision frame grabbers to review available acquisition options. Gidel PCIe GigE Vision Frame Grabbers Need help selecting the right acquisition, FPGA processing, networking, and synchronization architecture for your GigE Vision camera system? Contact Us. - Published: 2026-08-25 - Modified: 2026-09-07 - URL: https://gidel.com/coaxpress-cameras/ - Categories: Technical Articles - Tags: CXP-12, Image Processing, High-Resolution Imaging, Machine Vision, FPGA Processing, Image Acquisition, CoaXPress Cameras, CoaXPress Frame Grabbers, Multi-Camera Synchronization, Edge AI, Image Signal Processing, Line-Scan Imaging Selecting the right CoaXPress camera involves more than resolution and frame rate. Learn about CXP-6 and CXP-12 configurations, multi-link bandwidth, synchronization, acquisition architecture, and FPGA processing for high-speed imaging systems. High-Speed CoaXPress Cameras CoaXPress cameras are designed for high-speed, high-resolution imaging applications that require deterministic image transfer, precise triggering, and scalable bandwidth. The CoaXPress interface combines high-speed image transmission, camera control, triggering, and optional power over coaxial cable, making it well suited for demanding machine vision, scientific imaging, medical, defense, inspection, and multi-camera applications. Modern CXP-12 cameras can transmit up to 12. 5 Gb/s per CoaXPress link, while multi-link camera configurations can combine multiple links to increase the available interface bandwidth. A four-link CXP-12 configuration provides up to 50 Gb/s of aggregate interface bandwidth, while higher-link-count acquisition architectures can scale further. Selecting the correct CoaXPress camera therefore involves more than resolution and frame rate. Engineers must also consider the required number of CXP links, pixel depth, sensor architecture, triggering requirements, cable distance, frame grabber connectivity, host bandwidth, and downstream image-processing requirements. When Is CoaXPress the Right Camera Interface? CoaXPress is particularly well suited to imaging systems that require very high deterministic point-to-point bandwidth, precise triggering, and scalable multi-link acquisition. CXP-12 provides up to 12. 5 Gb/s per link, allowing one-, two-, and four-link cameras to scale according to the required image-data rate. The interface is especially attractive for high-resolution area-scan cameras, high-speed line-scan cameras, synchronized imaging, and applications where predictable transfer and direct frame-grabber connectivity are critical. For systems that prioritize standard Ethernet infrastructure, switched networking, or substantially longer distributed connections, another camera interface may be more appropriate. Understanding CXP Cameras CoaXPress, commonly abbreviated CXP, is a point-to-point high-speed imaging interface that transmits data over standard coaxial cable. Often referred to simply as a CoaXPress cable or CXP cable, this single connection provides a high-speed downlink from camera to acquisition hardware together with a lower-speed control uplink, precise triggering, and optional Power over CoaXPress (PoCXP). The standard also supports GenICam-based camera control. The Japan Industrial Imaging Association (JIIA) plays an important role in the development and standardization of CoaXPress. Its CoaXPress Working Group develops technical specifications and documentation, manages conformance and interoperability testing, and maintains a registration program for CoaXPress-compliant cameras, frame grabbers, cables, and related products. A key advantage of CoaXPress is scalability. A camera may use a single CXP connection or combine multiple links when the sensor produces more image data than one link can carry. CoaXPress cameras may operate at different link speeds, including CoaXPress-6 cameras (CXP-6 cameras) and CoaXPress-12 cameras (CXP-12 cameras), depending on the camera generation, required bandwidth, and acquisition architecture. Typical considerations include: Camera resolution and frame rate Number of CXP links CXP link speed Monochrome or color operation Pixel depth Global or rolling shutter External triggering and synchronization PoCXP requirements Cable length Area-scan or line-scan architecture Frame grabber and host-system bandwidth Current CoaXPress camera portfolios include both area-scan and line-scan models. For example, commercially available CXP-12 line-scan cameras include 8K and 16K sensors, while area-scan families range from relatively low resolutions to tens or even more than 100 megapixels. CoaXPress Camera Selection Criteria Select the CoaXPress camera according to the complete imaging workload, not interface speed alone. Resolution and Sensor Format Higher-resolution sensors capture more spatial detail but generate larger image payloads. The optical format and lens must also match the sensor size and required field of view. Global vs. Rolling Shutter Global-shutter cameras expose the complete image simultaneously and generally suit fast-moving objects and precision measurement. Rolling-shutter sensors may provide advantages in resolution, sensitivity, cost, or sensor availability, but motion artifacts must be considered for dynamic scenes. Frame Rate Higher frame rates directly increase the required data bandwidth. A camera that can operate at a high nominal frame rate may therefore require multiple CXP-12 links to transmit uncompressed image data at full performance. Pixel Depth and Image Format 8-, 10-, 12-, or higher-bit pixel formats affect image quality, dynamic range, and data rate. Color cameras may also increase the data volume depending on the transmitted pixel representation. Link Count A critical design parameter is whether the camera uses one, two, or four CoaXPress links, while higher-link-count acquisition architectures can scale further when required. The acquisition platform must provide enough compatible CXP connections for the camera configuration. Triggering and Synchronization Applications involving multiple cameras, moving objects, metrology, 3D reconstruction, or line-scan acquisition often require deterministic trigger timing and precise synchronization between sensors. Acquisition and Processing Architecture The camera is only one part of the data path. The frame grabber, FPGA, PCIe interface, host memory, storage subsystem, GPU, and processing pipeline must all sustain the actual image-data rate. Systems that prioritize long cable reach, standard Ethernet infrastructure, or switched multi-camera networking may instead evaluate GigE Vision cameras. Evaluating Bandwidth for High-Resolution and High-Speed Imaging High-resolution and high-speed CoaXPress cameras can generate extremely large continuous image streams, particularly in multi-link CXP-12 configurations. The required CXP link speed and link count should therefore be evaluated against resolution, frame rate, pixel depth, and camera count. The required acquisition bandwidth can be estimated from four primary factors: Resolution × frame rate × pixel depth × number of cameras = required image-data bandwidth For example, increasing resolution without changing frame rate increases the amount of data in every frame. Increasing frame rate raises the number of frames transmitted each second. Increasing pixel depth further increases the amount of data per pixel. A multi-camera system multiplies those requirements again. This is why engineers should never evaluate a camera specification independently of the acquisition architecture. Modern CXP-12 cameras span a wide range of possible designs, from compact single-link configurations to multi-link architectures supporting very high resolutions and frame rates. Four-link CXP-12 cameras can provide up to 50 Gb/s of aggregate interface bandwidth, while higher-link-count acquisition architectures can scale further when required. For high-resolution or high-speed applications, the frame grabber and downstream processing system must sustain the required data flow without introducing frame loss, excessive latency, or host-side processing bottlenecks. CXP-12 Camera Configurations and Multi-Link Bandwidth CXP-12 is the high-speed mode associated with CoaXPress 2. 0 and supports up to 12. 5 Gb/s per link. CXP-12 Link Configuration and Maximum Aggregate Bandwidth Configuration Maximum Aggregate Link Bandwidth 1 × CXP-12 12. 5 Gb/s 2 × CXP-12 25 Gb/s 4 × CXP-12 50 Gb/s 8 × CXP-12 Acquisition Architecture 100 Gb/s Swipe horizontally to view all columns → The number of links required depends on the camera's output architecture and image-data rate. A one-link CXP-12 camera can simplify cabling for moderate bandwidths, while two- and four-link designs are common in high-resolution and high-frame-rate systems. Higher-link-count acquisition architectures, including 8 × CXP-12 acquisition configurations, can scale aggregate interface bandwidth up to 100 Gb/s when required. CoaXPress Selection by System Requirement CoaXPress System Design Guide Requirement Typical CoaXPress Direction Moderate CXP-12 bandwidth 1 × CXP-12 Higher-resolution or higher-frame-rate imaging 2 × CXP-12 Very high camera throughput 4 × CXP-12 High aggregate multi-camera acquisition bandwidth Multi-link / multi-board CXP architecture Deterministic point-to-point image transfer CoaXPress with dedicated frame grabber Camera power through coaxial cable PoCXP-capable camera and frame grabber Compact CXP-12 connectivity Micro-BNC-based architecture Precise multi-camera synchronization Hardware-triggered synchronized acquisition Reduced host processing or data volume FPGA preprocessing in acquisition path Swipe horizontally to view all columns → Choosing the Right CoaXPress Connectivity and Cabling Cable Length CoaXPress supports cable lengths that vary with link speed. The official CoaXPress technical summary notes operation beyond 100 m at lower CXP speeds and approximately 35 m at 12. 5 Gb/s, depending on the quality of the CXP cable and the system implementation. Physical Connectors Micro-BNC is commonly used in compact CXP-12 cameras and acquisition hardware, while DIN 1. 0/2. 3 and BNC connectors are also used across CoaXPress systems. The connector type must match the camera, cable, frame grabber, and required link speed. Power over CoaXPress PoCXP allows compatible cameras to receive power through the same coaxial connection used for image transfer, reducing separate camera-power cabling. This makes CXP-12 cameras attractive where engineers need both high bandwidth and more practical camera placement than very short-reach interfaces permit. CoaXPress Limits and Design Considerations Frame Grabber Requirement CoaXPress cameras require compatible acquisition hardware that supports the camera's CXP link speed, link count, triggering, and PoCXP requirements. Link Count and Cabling Multi-link cameras increase aggregate bandwidth but also increase the number of coaxial connections between the camera and acquisition system. Cable Reach at Maximum Link Speed Maximum practical cable distance decreases as CXP link speed increases. CXP-12 installations therefore require appropriate cable quality and system validation, particularly at longer distances. Aggregate Acquisition Bandwidth A multi-link or multi-camera system can generate substantially more data than a single PCIe path, host memory subsystem, storage system, or GPU pipeline can sustain. The complete acquisition architecture must therefore be sized for aggregate throughput. Interface Architecture CoaXPress is optimized for deterministic point-to-point acquisition rather than switched network topologies. Systems built around established Camera Link cameras may instead use a direct frame-grabber architecture based on Base, Medium, Full, or Deca Camera Link configurations. Example Applications High-Speed Industrial Inspection CoaXPress cameras are well suited to inspection systems where objects move rapidly and image acquisition must remain deterministic. High frame rates combined with global-shutter sensors can capture detailed images without sacrificing throughput. High-Resolution Imaging Applications such as semiconductor inspection, electronics inspection, aerial imaging, medical imaging, and scientific instrumentation can produce extremely large image streams. CoaXPress provides the bandwidth required to move these images from the camera into the processing system. Line-Scan Imaging High-resolution line-scan cameras can generate substantial continuous bandwidth. Commercial CXP-12 line-scan cameras are available at 8K and 16K resolutions with high line rates, making the interface relevant to web inspection, sorting, printing, and surface inspection. Multi-Camera Vision CoaXPress supports deterministic triggering and scalable multi-link acquisition, making it suitable for synchronized multi-camera systems used for 3D imaging, multi-view inspection, volumetric capture, and sensor arrays. Defense, Aerospace and Outdoor Imaging High-bandwidth image acquisition, deterministic timing, robust coaxial connectivity, and long cable options can make CXP cameras suitable for mission-critical and remote-sensor imaging architectures. Edge AI and Real-Time Analytics High-resolution cameras can generate substantially more data than an embedded GPU should process indiscriminately. FPGA preprocessing, ROI selection, Compression, and other data-reduction functions can therefore be useful before AI inference. Modern CoaXPress Camera Vendors & Configurations The current market illustrates how broadly CoaXPress is being used across high-speed area-scan, high-resolution, line-scan, and rugged imaging applications. Basler offers CXP-12 camera families covering a broad range of resolutions and frame rates, including single-, dual-, and four-link configurations for high-speed machine vision applications. Allied Vision delivers CoaXPress-12 cameras using up to four parallel CXP-12 links, supporting aggregate interface bandwidth of up to 50 Gb/s for demanding high-speed and high-resolution imaging applications. KAYA Instruments supports industrial imaging applications with CoaXPress cameras that leverage CXP-12 interfaces to deliver high resolutions and frame rates for machine vision, defense, and high-speed outdoor imaging. Hamamatsu Photonics offers high-sensitivity scientific cameras with CoaXPress interfaces, including sCMOS and qCMOS systems used in demanding research applications. Its ORCA-Quest 2 qCMOS camera supports high-speed CoaXPress readout and is used in quantum technology applications such as neutral-atom and trapped-ion imaging, where ultra-low noise and photon-level sensitivity are critical. OMRON SENTECH provides CoaXPress cameras for both area-scan and line-scan imaging, including high-resolution 8K and 16K line-scan configurations. High-Speed CoaXPress Cameras The important system-design question is therefore not simply whether a camera uses CoaXPress, but how many links it requires, at what speed, and how much sustained image data the complete acquisition and processing pipeline must handle. CoaXPress Acquisition Platforms and FPGA Processing Once the camera requirements are defined, the next step is selecting an acquisition and processing architecture that can support the required CXP link count, bandwidth, synchronization, and real-time image-processing needs. Gidel provides PCIe CoaXPress frame grabbers and compact Edge AI systems for CoaXPress camera acquisition, with options for inline FPGA processing and scalable multi-camera synchronization. PCIe Frame Grabbers for CoaXPress Cameras High-speed CoaXPress cameras require acquisition hardware that matches the camera's CXP link count, link speed, synchronization requirements, and sustained data rate. A CoaXPress frame grabber receives image data from the camera, handles camera control and synchronization, buffers the acquisition stream where required, and transfers the image data into the host computer through PCIe. Gidel's portfolio of PCIe CoaXPress frame grabbers supports a range of camera configurations: HawkEye-CXP12: up to 4 × CoaXPress-12 links with PoCXP in a compact design, with an optional low-profile form factor Proc10A-CXP: up to 8 × CoaXPress-6 links with PoCXP Proc1C10N-CXP12: up to 8 × CoaXPress-12 links with PoCXP Gidel's CoaXPress frame-grabber family supports optional inline FPGA processing directly in the acquisition path for both CoaXPress-6 (CXP-6) and CoaXPress-12 (CXP-12) configurations. Edge AI Systems with CoaXPress Frame Grabbers Applications that benefit from a compact embedded architecture can use an integrated Edge AI system instead of a conventional host computer with a PCIe frame grabber. Gidel's FantoVision40-CXP12 combines an NVIDIA Jetson processor, Altera FPGA, and integrated Quad CXP-12 acquisition in a compact system. It supports 4 × CXP-12 links with PoCXP. The system combines FPGA-based camera acquisition and preprocessing with NVIDIA Jetson CPU/GPU computing for AI inference and application processing. Gidel FantoVision40-CXP12 Mini Edge AI System This creates two distinct architecture options: Gidel PCIe CoaXPress frame grabber:Installed in a host computer and provides CoaXPress camera acquisition, optional FPGA processing, and high-speed data transfer through PCIe to the host system for further processing, storage, and application execution. Gidel Mini Edge AI system with CoaXPress frame grabber:A complete compact embedded vision system that integrates CoaXPress camera acquisition, FPGA processing, and NVIDIA Jetson CPU/GPU computing in one platform. It is designed for applications that benefit from an integrated Edge AI architecture rather than a separate host computer with a PCIe acquisition card. For applications requiring both GigE Vision and CoaXPress cameras, the FantoVision40 combines optional Quad 10 GigE Vision and Quad CXP-12 acquisition support. Real-Time FPGA Image Processing for CoaXPress Acquisition High-speed cameras can produce more data than the host application needs in its raw form. Gidel FPGA-based acquisition platforms can optionally process image data as it is acquired, before host-side processing. Available functions include Compression, Detection, ROI/data reduction, custom FPGA processing, and other real-time image-processing operations. Processing data directly in the acquisition path can help: Reduce host bandwidth and storage requirements Lower host CPU/GPU load Preserve low-latency operation Execute deterministic processing Reduce data volume before recording, streaming, or AI inference This becomes increasingly relevant as CoaXPress-12 cameras scale toward multi-link, multi-camera, and high-resolution configurations. ISP and Image Enhancement Beyond general FPGA processing, high-speed CoaXPress cameras often require dedicated ISP and image-enhancement functions before display, recording, analysis, or AI inference. When these functions are not already implemented inside the camera, they can often be implemented in the FPGA acquisition path, reducing the amount of ISP processing that must be handled later by the host CPU or GPU. Depending on the sensor type and application, common ISP and image-enhancement functions may include debayering, white balance, gain and offset correction, HDR correction, bad-pixel correction, non-uniformity correction, dynamic luminance balancing, and color or luminance optimization. Gidel acquisition platforms can integrate selected ISP and image-processing functions directly into the FPGA acquisition path. These functions may be based on Gidel's existing processing capabilities, customer-specific requirements, or custom algorithms developed for the application. Running ISP functions inline during acquisition can preserve low latency, reduce host processing load, and prepare image data earlier in the pipeline for recording, streaming, visualization, analysis, or AI processing. This is especially valuable in high-resolution and multi-camera CoaXPress systems, where implementing part of the ISP workload in deterministic FPGA hardware can reduce host CPU/GPU processing requirements, simplify system design, and improve end-to-end efficiency. Building Your Own ISP with Gidel Platforms Gidel platforms provide several ways to build and customize an FPGA-based ISP pipeline. Customers can use Gidel's off-the-shelf image-processing algorithms, integrate their own FPGA algorithms, develop new processing functions using Gidel's ProcVision Suite, or work with Gidel to develop application-specific algorithms. These approaches can also be combined within the same processing pipeline, allowing existing Gidel functions, customer-developed IP, and newly developed algorithms to operate together directly in the FPGA acquisition path. Using ProcVision Suite, experienced FPGA developers can implement and integrate application-specific processing stages such as debayering, gain and offset correction, HDR, image enhancement, ROI handling, Detection, Compression, and other custom processing functions. This flexibility allows the processing pipeline to be tailored to the camera, sensor, and application requirements while executing deterministically in the FPGA before data reaches the host CPU, GPU, or Jetson processor. Multi-Camera Synchronization and Scalable Acquisition Multi-camera CoaXPress systems require more than sufficient aggregate bandwidth. Frames must also be acquired with deterministic timing and controlled synchronization. Gidel's InfiniVision architecture is designed for scalable synchronized acquisition across multiple cameras and acquisition systems. Current Gidel CXP platforms support configurations scaling to 100+ synchronized CXP cameras while retaining FPGA-based data handling. This architecture is relevant to applications such as: Synchronized multi-view imaging Volumetric imaging 3D vision High-speed sensor arrays Large inspection systems Defense and scientific imaging Distributed acquisition systems CoaXPress Camera Alternative for Development and Validation During early-stage development, system integration, and validation, engineers may not always have access to the final CoaXPress camera or may need repeatable image streams that are difficult to reproduce with a physical camera. A CoaXPress camera simulator can generate controlled video streams and test patterns, allowing frame grabbers, processing pipelines, triggering, and system behavior to be validated under repeatable conditions. Gidel's CamSim-X is a CoaXPress camera simulator supporting up to four CoaXPress-12 output links at up to 12. 5 Gb/s per link. It can generate programmable CoaXPress image streams and provides a practical alternative to physical CXP cameras during development and validation. So, Which CoaXPress Camera Is Right for You? There is no single “best” CoaXPress camera for every application. The right choice depends on the balance between sensor requirements, CXP link architecture, acquisition bandwidth, synchronization, and downstream processing capacity. High-Speed Line-Scan Inspection:Consider 8K or 16K CXP-12 line-scan cameras paired with acquisition hardware capable of sustaining the required line rate and image-data bandwidth without frame loss. Ultra-High-Resolution Imaging:Multi-link CXP-12 area-scan cameras using two or four links can provide the bandwidth required for high-resolution, high-frame-rate acquisition. The frame grabber and host architecture must be sized for the resulting sustained data rate. Multi-Camera and Volumetric 3D Imaging:Prioritize cameras and acquisition platforms that support deterministic triggering and synchronization. For larger systems, scalable synchronization architectures such as Gidel InfiniVision can coordinate acquisition across multiple cameras and systems. Compact and Embedded Deployments:CoaXPress cameras can be paired with integrated Edge AI platforms combining FPGA-based acquisition with NVIDIA Jetson CPU/GPU processing, reducing the need for a separate host computer and PCIe acquisition card. High-Throughput and Data-Intensive Pipelines:Consider an acquisition platform with inline FPGA processing for functions such as Compression, ISP, HDR, Detection, or data reduction. Processing data during acquisition can reduce host bandwidth, storage requirements, and downstream CPU/GPU processing load. Need help configuring your CoaXPress acquisition and processing pipeline? Explore Gidel's PCIe CoaXPress frame grabbers to review available acquisition options. Gidel PCIe CoaXPress Frame Grabbers Need help selecting the right acquisition, FPGA processing, and synchronization architecture for your CoaXPress camera system? Contact Us. - Published: 2026-07-20 - Modified: 2026-08-27 - URL: https://gidel.com/skyboost-accelerating-aerial-photogrammetry-post-processing/ - Categories: Technical Articles, Press release, Company Updates - Tags: High-Resolution Imaging, FPGA Processing, Aerial Mapping, Aerial Photogrammetry, Batch Processing, Image Signal Processing, FPGA Compression High-resolution aerial mapping missions can generate thousands of RAW images that take hours or even days to process. Discover how SkyBoost uses FPGA acceleration to reduce post-flight processing time by up to 50x while maintaining image quality for orthophoto production and 3D photogrammetry. SkyBoost Accelerates Aerial Photogrammetry Post-Processing Gidel, a technology leader in FPGA-based imaging and vision solutions, today announced the launch of SkyBoost, an FPGA hardware accelerator designed to accelerate aerial photogrammetry post-processing. By offloading computationally intensive RAW-to-JPEG conversion to a dedicated FPGA hardware accelerator, SkyBoost helps aerial mapping teams transform large post-flight datasets into analysis-ready aerial imagery far faster than software-only workflows. What Is Aerial Photogrammetry? Aerial photogrammetry uses overlapping images captured from aircraft or drones to create accurate maps, orthophotos, point clouds, elevation models, and 3D reconstructions. A typical workflow includes image capture, transfer of the aerial dataset, image preparation and processing, photogrammetric reconstruction, and generation of mapping or 3D deliverables. As camera resolution and mission size increase, the image-preparation stage can become a significant bottleneck. Aerial surveys may generate hundreds or thousands of high-resolution RAW images that must be corrected, converted, and compressed before they can efficiently enter orthophoto, mapping, or 3D photogrammetry software. SkyBoost is designed to accelerate this high-resolution image-preparation and post-processing bottleneck before photogrammetric reconstruction. Solving the Industrial-Scale RAW-to-JPEG Backlog In high-end surveying, the bottleneck often shifts from the aircraft to the office as soon as a mission ends. A single flight can generate thousands of high-resolution RAW files, creating a backlog that ties up workstations and delays deliverables. SkyBoost addresses this by moving conversion and image processing into dedicated FPGA hardware, so post-processing is no longer the weakest link in the workflow. Accelerating High-Volume Aerial Photogrammetry and Drone Mapping Workflows SkyBoost is engineered for the throughput requirements of modern high-resolution sensors as drone mapping and UAV mapping projects scale toward higher resolutions and larger datasets. In batch mode, SkyBoost performs high-volume processing of high-resolution RAW (Bayer) data directly from local storage and delivers total throughput of over 1 Terapixel per hour. This enables organizations to process terabytes of aerial imagery in less than an hour, maintaining speeds of over 3 images per second for 100MP sensors and over 2 images per second for 150MP sensors. Advanced FPGA ISP Pipeline for Precision Orthophoto and 3D Photogrammetry Quality is not sacrificed for speed. SkyBoost uses an FPGA-based Image Signal Processing (ISP) pipeline that runs deterministically to support consistent results for orthophoto and 3D photogrammetry workflows, especially in outdoor imaging conditions with challenging lighting and high dynamic range scenes. The pipeline includes high-quality demosaicing to convert Bayer data into sharp RGB imagery, HDR correction for high-contrast lighting, and chromatic aberration correction to reduce color fringing. It also includes Non-Uniformity Correction (NUC) and Bad Pixel Replacement (BPR) to help maintain uniform image quality across the sensor. SkyBoost supports ultra-high-resolution sensors up to approximately 500MP, including image widths up to 32K pixels. Why FPGA for Aerial Photogrammetry? Unlike CPU-based image processing, SkyBoost performs deterministic FPGA image processing with predictable throughput, enabling organizations to process extremely large aerial imaging datasets while maintaining consistent image quality and freeing workstation resources for other tasks. SkyBoost is built entirely on Gidel's in-house FPGA platform and can be customized using the ProcVision SDK or expanded with additional FPGA image processing IPs to meet specific application requirements. Why Choose SkyBoost for Aerial Photogrammetry? Accelerate project turnaround times from days to minutes by processing over 1 Terapixel per hour. Convert RAW Bayer data to high-quality JPG images up to 50x faster than software-only workflows. Offload computationally intensive image processing to dedicated FPGA hardware. Maintain industrial-scale throughput for demanding datasets, including support for sensors up to ~500MP and 32K pixel widths. Enhance image quality using a deterministic FPGA-based ISP pipeline that includes white balance, dynamic luminance balance, NUC, BPR, HDR, and chromatic aberration correction. Customize the ISP pipeline using ProcVision SDK to meet specific project imaging requirements. Where SkyBoost Fits in the Aerial Photogrammetry Workflow Aerial Photogrammetry Workflow and SkyBoost Role Aerial Photogrammetry Stage Typical Function SkyBoost Role Image capture Aircraft or drone captures overlapping high-resolution imagery No Data transfer RAW imagery is copied to workstation or server storage No Image preparation Demosaicing, correction, enhancement, and RAW conversion Yes JPEG compression Convert large RAW datasets into efficient JPEG image files Yes Photogrammetric reconstruction Feature matching, triangulation, point-cloud and 3D generation Performed by photogrammetry software Final deliverables Orthophotos, maps, elevation models, and 3D models Consumes processed imagery Swipe horizontally to view all columns → SkyBoost integrates into the post-capture phase of professional mapping missions: Data Capture: Teams capture high-resolution RAW or mono imagery during the flight mission. Data Transfer: Teams copy datasets from aircraft media to local or server storage. Batch Ingest: The user selects a folder of RAW files for batch conversion of RAW images into high-quality JPEG output. Processing Profile: The user selects the processing preset and output settings, for example demosaicing, white balance, dynamic luminance balance, and JPEG quality. Hardware Offloading: SkyBoost performs the processing using its dedicated FPGA processing engine rather than the host CPU. Deterministic ISP: The hardware applies the selected correction pipeline, including image normalization, based on configuration. High-Speed Compression: The engine performs JPEG compression with ratios exceeding 10:1, depending on scene content and quality settings. Final Output: Processed images are saved for immediate use in orthophoto and 3D photogrammetry software. Aerial Photogrammetry Applications Aerial mapping Orthophoto production Ultra-high-resolution aerial imaging 3D modeling and 3D photogrammetry Smart cities Post-disaster assessment Large-scale inspection Environmental monitoring Precision agriculture Drone mapping and UAV mapping Watch SkyBoost in Action See how SkyBoost accelerates aerial photogrammetry post-processing by converting high-resolution RAW imagery into JPEG outputs through a dedicated FPGA-based processing pipeline. This exhibition demo shows the image-processing flow from RAW input to JPEG output, with the RAW images displayed on the left and the generated JPEG results displayed on the right. The demo illustrates accelerated RAW image processing and JPEG generation for mapping and photogrammetry applications. Note: Performance figures are based on Gidel internal benchmarking in batch mode under controlled conditions. Actual results may vary depending on dataset characteristics, selected ISP options, storage bandwidth, and host system configuration. SkyBoost Deployment Options SkyBoost is available as a PCIe FPGA accelerator for Windows and Linux workstations and servers. The same FPGA image processing pipeline can also be deployed on Gidel's FantoVision system when a compact, stand-alone embedded solution is required. Accelerating the Future of Aerial Photogrammetry As aerial imaging sensors continue to increase in resolution, post-flight processing is becoming a critical bottleneck for mapping and photogrammetry organizations. SkyBoost addresses this challenge by combining deterministic FPGA image processing with high-throughput JPEG compression, significantly reducing project turnaround times while maintaining consistent image quality across large aerial datasets. Whether processing hundreds or thousands of high-resolution aerial images, SkyBoost enables surveying, mapping, and geospatial professionals to move from data capture to analysis faster. Its scalable FPGA architecture also helps organizations keep pace with growing dataset sizes, higher sensor resolutions, and increasingly demanding photogrammetry workflows. Explore Gidel SkyBoost Schedule a Demo Visit Geo Week for Industry News Real-Time Aerial Imaging Processing During Acquisition While SkyBoost accelerates post-flight batch processing, some airborne imaging systems must process, compress, record, or stream high-resolution imagery during the mission. For these real-time workflows, SkyBoost-RT performs FPGA-based ISP and compression directly during image acquisition, helping reduce onboard storage, processing, and downlink bandwidth requirements. Learn how SkyBoost-RT enables real-time aerial imaging processing during acquisition - Published: 2026-07-13 - Modified: 2026-08-31 - URL: https://gidel.com/real-time-aerial-imaging-processing-skyboost-rt-award/ - Categories: Technical Articles, Press release - Tags: High-Resolution Imaging, UAV, Aerial Imaging, Aerospace, FPGA Processing, ISR, Recording & Streaming, CoaXPress Frame Grabbers, Edge AI, Image Signal Processing, GigE Vision Frame Grabbers, Camera Link Frame Grabbers, FPGA Compression Gidel SkyBoost-RT has been recognized as a Vision Systems Design 2026 Innovators Awards Silver Honoree. This real-time aerial imaging processing solution uses FPGA-based ISP and compression during RAW image acquisition, reducing storage and downlink bandwidth bottlenecks for ISR, aerial mapping, aerial inspection, search and rescue, and situational awareness applications. Real-Time Aerial Imaging Processing Recognized in the 2026 VSD Innovators Awards Vision Systems Design recognized Gidel’s SkyBoost-RT as a Silver Honoree in the 2026 Innovators Awards for its real-time aerial imaging processing capabilities. The recognition highlights SkyBoost-RT’s FPGA-based approach to airborne Image Signal Processing (ISP) and compression for aerial imaging, ISR, and inspection workflows. SkyBoost-RT is designed for applications where high-resolution sensors generate massive RAW data streams that airborne systems must process, record, or stream during the mission. By combining deterministic FPGA processing, low latency, and high-ratio compression, it helps reduce onboard storage, bandwidth, and processing bottlenecks. SkyBoost-RT Real-Time Aerial Imaging Processing Capabilities Capability SkyBoost-RT Processing mode Real-time FPGA ISP and compression during acquisition Image size Up to ~500MP per image Image width Up to 32K pixels 100MP throughput More than 7 images per second 150MP throughput More than 4. 5 images per second Processing volume More than 2 terapixels per hour JPEG compression Compression ratio exceeding 10:1, depending on configuration and image content Camera interfaces GigE Vision, CoaXPress, Camera Link, and custom interfaces Swipe horizontally to view all columns → Real-Time FPGA ISP for Aerial Imaging and ISR SkyBoost-RT processes high-resolution RAW Bayer image data while the camera is actively capturing. Instead of waiting for intensive post-processing after the mission, SkyBoost-RT enables the system to generate, compress, record, or stream high-quality imagery in real time. The FPGA-based pipeline can include demosaicing, HDR correction, chromatic aberration correction, Non-Uniformity Correction (NUC), Bad Pixel Replacement (BPR), Dynamic Luminance Balance, White Balance, and additional mission-specific ISP stages. Reducing Storage and Downlink Bandwidth Bottlenecks In airborne imaging systems, storing or transmitting uncompressed RAW data is often impractical. High-resolution sensors can quickly generate terabytes of data, creating major challenges for onboard storage, downlink bandwidth, and real-time usability. SkyBoost-RT addresses this challenge by compressing image data directly on the FPGA during acquisition. JPEG compression can often exceed a 10:1 compression ratio, significantly reducing data volume while maintaining high image quality. Optional H. 264 / H. 265 and RTSP output options can also support efficient video streaming and recording workflows. High-Resolution Airborne Sensor Processing SkyBoost-RT supports large-format aerial imaging applications, including image widths up to 32K pixels and sensor classes up to approximately 500MP per image, depending on camera model and configuration. In real-time pipelines, the system can process over 7 images per second, depending on configuration and input format. This enables continuous acquisition, ISP, compression, recording, and streaming without interrupting the image stream. Aerial Imaging and Inspection Workflows Beyond defense ISR, SkyBoost-RT can support aerial inspection, mapping, search and rescue, and situational awareness applications where high-resolution image capture must be combined with immediate processing, compression, recording, or streaming. This helps airborne platforms convert massive RAW sensor data into usable visual information during the mission, not only after landing. Deployment Across UAVs, Aircraft, and Embedded Payloads SkyBoost-RT supports deployment across Gidel’s FPGA accelerator platforms, including PCIe frame grabbers installed in PCs or servers, compact FPGA modules for embedded and low-SWaP systems, and FantoVision Mini Edge AI systems that combine NVIDIA Jetson computing with FPGA-based image acquisition and processing. The solution supports high-end GigE Vision frame grabbers, CoaXPress frame grabbers, and the Camera Link frame grabber, as well as custom sensor interfaces. It also integrates with Gidel’s Grabber SDK suite and supports camera control through GenICam GenTL. Engineers evaluating camera selection can also review Gidel’s guides to GigE Vision cameras, CoaXPress cameras, and Camera Link cameras to compare bandwidth, link configuration, cabling, synchronization, and acquisition requirements. Custom ISP Pipelines for Mission-Specific Imaging Requirements For advanced users, the ProcVision Suite enables full ISP pipeline customization at the FPGA level. This lets engineers optimize the processing flow for image quality, compression ratio, throughput, latency, and system resource utilization. The SkyBoost-RT award reinforces the value of real-time FPGA processing for airborne imaging teams that need to process, compress, record, and stream massive RAW data directly at the point of acquisition. Explore Gidel SkyBoost-RT Read the Full Vision Systems Design Announcement Post-Flight: Accelerating the RAW-to-JPEG Backlog While SkyBoost-RT handles real-time acquisition in the air, capturing high-resolution aerial data is only the first half of the mission. Once the UAV lands, the bottleneck often shifts to batch post-processing. For organizations dealing with thousands of offline RAW images, Gidel's standard SkyBoost operates as a dedicated PCIe FPGA accelerator, converting RAW (Bayer) files to JPEG up to 50x faster than software-only workflows. Learn how SkyBoost accelerates aerial photogrammetry post-processing - Published: 2026-06-16 - Modified: 2026-08-31 - URL: https://gidel.com/israel-machine-vision-conference-imvc-2026-gidel/ - Categories: Events - Tags: Embedded Vision, High-Resolution Imaging, Machine Vision, FPGA Processing, CoaXPress Frame Grabbers, Edge AI, FPGA Compression, IMVC 2026, High-Speed Imaging At IMVC 2026, Gidel demonstrated FPGA imaging solutions featuring embedded AI vision, multi-sensor CoaXPress-12 acquisition, FPGA processing, Quality+ Compression, and high-resolution image acceleration. See how Gidel FPGA platforms reduce CPU/GPU workload across real-time acquisition and post-processing workflows. IMVC 2026: Gidel Demonstrated Real-Time FPGA Imaging and Edge AI At IMVC 2026, Gidel demonstrated two live FPGA-based imaging workflows covering real-time acquisition, embedded AI, and high-resolution image processing. The demonstrations showed how FPGA acceleration can reduce CPU/GPU workload, improve deterministic image processing, and support demanding machine vision applications. Real-Time Embedded Imaging & AI Solution FantoVision40-CXP12: Mini Edge AI System with FPGA The FantoVision40-CXP12 demo presented a complete embedded AI vision pipeline combining FPGA-based image acquisition and processing with NVIDIA Jetson computing. The FPGA handled deterministic acquisition from multiple sensors, performed real-time preprocessing, and applied Gidel’s proprietary Quality+ Compression to reduce data volume before the Jetson handled AI workloads such as tracking, detection, and classification. The system acquired data in real time from two CoaXPress-12 cameras, one IR and one RGB Bayer, processing 13MP images at 30 FPS while maintaining high image quality. Engineers evaluating CoaXPress camera selection can also review Gidel’s guide to CoaXPress cameras to compare bandwidth, link count, cabling, synchronization, and acquisition requirements. High-Resolution Post-Processing Acceleration SkyBoost: High-Resolution RAW-to-JPEG Imaging Acceleration The second demonstration featured SkyBoost, Gidel’s FPGA-based imaging accelerator for very large images, including image sizes above 100MP. The demo used a PCIe FPGA accelerator installed in the host PC, with image processing running directly on the FPGA. This offloaded the main imaging workload from the host CPU or GPU and accelerated high-resolution post-processing. The same FPGA image processing pipeline can also be deployed on Gidel’s FantoVision system when a compact, stand-alone embedded solution is required. In the demonstrated workflow, SkyBoost reduced the processing time from 30 seconds or more per image to more than two images per second. This can significantly shorten high-resolution processing workflows that otherwise require hours or, in some cases, days. The technology accelerates analysis, reporting, and decision-making in demanding applications. These include defense, intelligence, aerial imaging, and mission-critical vision systems. SkyBoost supports host-based post-processing workflows, while SkyBoost-RT extends the FPGA processing approach to real-time image processing during acquisition. FPGA Frame Grabbers for CoaXPress, GigE Vision, and Camera Link Gidel also presented FPGA-based acquisition platforms for demanding machine vision and imaging systems. Gidel PCIe frame grabbers combine high-bandwidth camera acquisition with programmable FPGA resources for optional real-time image processing, image enhancement, compression, data reduction, and application-specific processing. Solutions included CoaXPress frame grabbers, GigE Vision frame grabbers, and the Camera Link frame grabber. FPGA Acceleration Across the Imaging Workflow The two IMVC 2026 demonstrations represented different stages of the imaging pipeline. FantoVision40-CXP12 showed how FPGA processing can operate directly at acquisition, handling camera input, preprocessing, compression, and data preparation before NVIDIA Jetson AI processing. SkyBoost demonstrated the complementary post-processing architecture, where FPGA hardware accelerates very large image datasets inside a host workstation or server. Together, these architectures show how Gidel FPGA platforms can offload demanding imaging tasks from the CPU and GPU, improve throughput, reduce system bottlenecks, and maintain predictable processing performance across both real-time and offline workflows. IMVC 2026 Event Details Monday, June 29, 2026 Pavilion 10, Booth 9, EXPO Tel Aviv Event link: IMVC 2026 - Published: 2026-05-27 - Modified: 2026-08-31 - URL: https://gidel.com/meet-gidel-at-embedded-technologies-conference-2026/ - Categories: Events - Tags: Embedded Vision, Machine Vision, FPGA Processing, Image Acquisition, Edge AI, GigE Vision Frame Grabbers, FPGA Compression, Embedded Technologies 2026, High-Speed Imaging At Embedded Technologies 2026, Gidel demonstrated FPGA-based imaging and embedded AI vision solutions. The FantoVision Edge AI platform combined 10 GigE Vision acquisition, FPGA processing, HDR, and Quality+ Compression to reduce CPU/GPU load and support real-time AI applications. Embedded Technologies 2026: Gidel Demonstrated FPGA Embedded AI Vision At Embedded Technologies 2026, Gidel demonstrated an FPGA-based embedded AI vision system designed for compact, high-performance imaging applications. The live demonstration showed how Gidel combines NVIDIA Jetson computing with FPGA processing to support high-speed image acquisition, deterministic real-time processing, HDR, compression, and AI at the edge. FantoVision20-GigE: Real-Time Embedded AI Vision Demo FantoVision20-GigE: NVIDIA Jetson + FPGA Edge AI Vision System The live demonstration featured FantoVision20-GigE, combining NVIDIA Jetson and FPGA technology in a compact Edge AI vision platform. The system demonstrated real-time 10 GigE Vision acquisition with FPGA-based image processing, advanced HDR, and Gidel’s proprietary Quality+ Compression. By performing image enhancement and compression on the FPGA, the system reduced the processing load on the NVIDIA Jetson, leaving more CPU/GPU resources available for real-time AI workloads such as detection, tracking, and classification. Engineers evaluating GigE Vision camera selection can also review Gidel’s guide to GigE Vision cameras to compare bandwidth, connectivity, cabling, synchronization, and acquisition requirements. Why FPGA Processing Matters for Embedded Vision Embedded AI systems often need to process high-resolution image streams within tight power, size, latency, and computing constraints. Gidel’s FPGA-based architecture processes image data close to acquisition before transferring it to the NVIDIA Jetson CPU/GPU. This can reduce latency and data volume while providing predictable, deterministic processing for demanding embedded vision applications. The architecture also allows image processing, enhancement, HDR, compression, and other application-specific functions to run in FPGA hardware while Jetson computing resources remain focused on AI inference and application processing. Embedded AI Vision Applications The architecture demonstrated at Embedded Technologies 2026 is relevant to applications including: Robotics and autonomous systems Smart mobility Industrial automation Machine vision Advanced sensing systems Embedded Edge AI High-speed image acquisition and processing Multi-camera imaging Explore Gidel FPGA Imaging Solutions FantoVision Edge AI Systems Real-Time HDR Correction Quality+ Compression Gidel PCIe Frame Grabbers Embedded Technologies 2026 Event Details Wednesday, June 17, 2026 Daniel Hotel, Herzliya - Published: 2026-04-20 - Modified: 2026-08-31 - URL: https://gidel.com/chipex2026-exhibition/ - Categories: Events - Tags: Embedded Vision, Machine Vision, FPGA Processing, Image Acquisition, CoaXPress Frame Grabbers, Edge AI, GigE Vision Frame Grabbers, Camera Link Frame Grabbers, FPGA Compression, High-Speed Imaging, ChipEx 2026 At ChipEx 2026, Gidel demonstrated FantoVision20-GigE with real-time 10 GigE Vision acquisition, single-exposure HDR, Quality+ Compression, and sub-frame FPGA processing. The demo showed how Gidel’s FPGA-based architecture reduces CPU/GPU workload and supports deterministic embedded AI vision systems. ChipEx 2026 Exhibition: Gidel Demonstrated FPGA Imaging and Embedded AI At the ChipEx 2026 Exhibition, Gidel demonstrated FPGA-based imaging and embedded AI vision technologies for high-performance acquisition, deterministic real-time processing, image enhancement, compression, and Edge AI applications. FantoVision20-GigE: Real-Time 10 GigE Vision Demo FantoVision20-GigE: NVIDIA Jetson + FPGA Edge AI Vision System The live demonstration featured Gidel’s FantoVision20-GigE, combining NVIDIA Jetson Orin NX computing with an Altera FPGA in a compact embedded vision platform. The system demonstrated real-time 10 GigE Vision acquisition together with FPGA-based image processing, advanced HDR, and Gidel’s proprietary Quality+ Compression. Key capabilities included: Real-time 10 GigE Vision acquisition for high-speed, low-latency imaging High-quality single-exposure HDR to improve visibility in dark regions while preserving detail in bright areas Quality+ Compression for efficient image-quality-to-compression performance Sub-frame latency enabled by FPGA-based processing By performing image enhancement and compression on the FPGA, the architecture reduces the processing burden on the NVIDIA Jetson and leaves more CPU/GPU resources available for AI workloads. Engineers evaluating GigE Vision camera selection can also review Gidel’s guide to GigE Vision cameras to compare bandwidth, connectivity, cabling, synchronization, and acquisition requirements. Why FPGA Processing Matters for Embedded AI Vision The ChipEx demonstration showed how FPGA processing can provide deterministic acquisition, low-latency image enhancement, compression, and application-specific processing before data reaches the Jetson CPU/GPU. This architecture is particularly useful in systems where camera bandwidth, latency, predictable processing, and efficient use of AI computing resources are critical. FPGA Frame Grabbers for High-Bandwidth Imaging Gidel also presented its FPGA-based frame grabber portfolio for demanding machine vision and imaging applications. Gidel PCIe frame grabbers combine high-bandwidth image acquisition with programmable FPGA resources for optional real-time processing, image enhancement, compression, data reduction, and application-specific processing. Solutions include CoaXPress frame grabbers, GigE Vision frame grabbers, and the Camera Link frame grabber. Applications for FPGA Imaging and Embedded AI The technologies demonstrated at ChipEx 2026 are relevant to applications including: Semiconductor inspection Industrial machine vision Embedded Edge AI High-speed image acquisition and processing Multi-camera imaging Defense imaging Advanced sensing systems Robotics and autonomous systems Explore Gidel FPGA Imaging Solutions FantoVision Edge AI Systems Real-Time HDR IP Core Quality+ Compression ChipEx 2026 Exhibition Event Details May 12, 2026 Pavilion 10, EXPO Tel Aviv - Published: 2026-01-01 - Modified: 2026-08-31 - URL: https://gidel.com/gidel-2025-milestones-edge-ai-vision/ - Categories: Company Updates - Tags: Embedded Vision, High-Resolution Imaging, Machine Vision, FPGA Processing, Image Acquisition, CoaXPress Frame Grabbers, Edge AI, GigE Vision Frame Grabbers, Camera Link Frame Grabbers, FPGA Compression Gidel’s 2025 milestones included three new FantoVision FPGA Edge AI systems, advances in high-resolution acquisition and low-latency imaging, Quality+ Compression recognition, and expanded global activity. Explore the FPGA imaging technologies and achievements that shaped Gidel’s year. Gidel 2025 Milestones Gidel’s 2025 milestones spanned FPGA imaging, Edge AI vision, high-resolution acquisition, low-latency processing, and real-time compression. The year also brought industry recognition and global expansion. During the year, Gidel launched three new FantoVision systems, advanced FPGA processing for high-resolution imaging, and earned recognition for Quality+ Compression. 1. Three New FPGA Edge AI Vision Systems We launched the new FantoVision series, delivering interface-specific optimization for developers requiring peak performance and determinism: FantoVision40-CXP12: Mini Ruggedized NVIDIA Jetson + Quad PoCXP-12 links, providing up to 50 Gb/s aggregate interface bandwidth, with an Altera FPGA frame grabber. FantoVision20-GigE: Mini Ruggedized NVIDIA Jetson + Dual 10 GigE Vision, providing up to 20 Gb/s aggregate interface bandwidth, with an Altera FPGA frame grabber. FantoVision20-CL: Mini Ruggedized NVIDIA Jetson + 80-bit Deca Camera Link, providing up to 6. 8 Gb/s interface bandwidth, with an Altera FPGA frame grabber. Engineers comparing camera interfaces can also review Gidel’s guides to CoaXPress cameras, GigE Vision cameras, and Camera Link cameras. The guides cover bandwidth, link configuration, cabling, synchronization, and acquisition considerations. 2. Mastering High-Resolution Acquisition & Low-Latency Imaging We released comprehensive solutions to tackle the toughest environmental and timing challenges: High-Resolution Outdoor Imaging: In partnership with illunis, we implemented real-time FPGA preprocessing (HDR, white balance, dynamic luminance balance) and on-the-fly 10× compression directly at the edge. This architecture managed massive 103 MP data streams with zero frame loss, reducing mission storage needs from 12 TB to 1. 2 TB. Adding System Performance Without Adding Latency: We optimized the imaging pipeline by offloading heavy computational tasks directly to the FPGA. These included demosaicing, HDR correction, compression, protocol parsing, and binning. This leaves the CPU available for higher-level decision logic while maintaining deterministic low latency and throughput exceeding 1 gigapixel per second. 3. Industry Recognition & Expansion Top Innovation Award: Our Quality+ Compression technology was honored with the inVISION Award 2025 for its ability to deliver Alternative Lossless Compression with uncompromised real-time image quality at compression ratios of 10:1 or higher. Strategic Partnership: We signed a new exhibitor agreement with 1stVision in the US to expand our reach in the vision and imaging market, while celebrating five years of collaboration with Viewsitec. Global Exhibitions: Gidel showcased its innovations worldwide, participating in: Vision China (Shanghai) IMVC (Tel-Aviv) ChipEX (Tel Aviv) Defense Solutions (Herzliya) Vision China (Beijing) Vision China (Shenzen) Military & Aviation (Tel Aviv) UVID DroneTech (Tel Aviv) Vision & AI (Tel Aviv) Building on Gidel 2025 Milestones in 2026 Gidel 2025 Milestones established a strong foundation for continued development in FPGA imaging and Edge AI vision. These developments also advanced Gidel’s capabilities in high-resolution acquisition, real-time processing, and compression. In 2026, Gidel will continue expanding these technologies across industrial, scientific, aerospace, defense, and mission-critical imaging applications. - Published: 2025-12-12 - Modified: 2026-08-31 - URL: https://gidel.com/edge-ai-vision-system/ - Categories: Technical Articles - Tags: Embedded Vision, Machine Vision, FPGA Processing, Image Acquisition, Recording & Streaming, CoaXPress Frame Grabbers, Edge AI, GigE Vision Frame Grabbers, Camera Link Frame Grabbers, FPGA Compression, High-Speed Imaging, NVIDIA Jetson, Altera FPGA Gidel expands FantoVision with three dedicated Edge AI Vision Systems for CoaXPress-12, 10 GigE Vision, and Camera Link. By combining NVIDIA Jetson Orin NX with FPGA-based acquisition and processing, FantoVision breaks the “Jetson I/O Wall,” reducing CPU acquisition load and preserving more Jetson resources for real-time AI applications. Gidel Expands FantoVision with Three Dedicated Edge AI Vision Systems After the groundbreaking success of the FantoVision20 and FantoVision40, combining NVIDIA Jetson Orin NX with FPGA AI accelerator technology, Gidel now introduces three dedicated models designed for applications requiring CoaXPress 12, 10 GigE Vision, or Camera Link. These systems do not replace existing capabilities. Instead, they offer optimized, interface-specific edge AI vision systems for developers who need maximum bandwidth, determinism, and sustained AI performance at the edge. The promise of Edge AI Vision is the ability to perform real-time inference directly at the point of image capture. The NVIDIA Jetson Orin NX, delivering up to 157 TOPS, provides substantial AI processing performance in a compact embedded form factor. Yet as modern imaging systems demand higher aggregate I/O bandwidth through increased resolution, higher frame rates, and simultaneous multi-camera acquisition, developers encounter a persistent bottleneck: "the Jetson I/O Wall". In practice, standard embedded computers struggle to handle raw, high-bandwidth video streams without overwhelming the CPU. The FantoVision family was designed specifically to solve this problem. Understanding the Jetson I/O Wall While the NVIDIA Jetson Orin NX delivers exceptional edge AI vision performance, its ability to ingest data is constrained by standard interfaces. As modern industrial cameras push far beyond 10 Gb/s and transmit millions of packets per second, the Jetson’s ARM CPU must process every interrupt, decode every packet, and rebuild every frame in software. As a result, this creates a hard limit on how much data the Jetson can accept before the CPU becomes saturated. Once this limit, the "I/O Wall", is reached, camera streams begin to drop frames, latency increases, and AI performance collapses due to CPU overload and thermal pressure. Gidel’s architecture addresses this bottleneck by moving packet handling, protocol termination, and raw data movement into a deterministic FPGA AI accelerator, expanding the practical limits of modern edge vision. CPU Load Wall: While standard systems saturate the CPU at high bandwidths, FantoVision’s FPGA offload keeps CPU load below 25%, breaking the I/O Wall. The Challenge: When Jetson Chokes on Pixels High-end Machine Vision Solutions, particularly those deploying edge vision AI, require not only compute power but also deterministic, high-bandwidth image acquisition. A typical embedded system forces the CPU to act as the frame grabber. With streams reaching 10 Gb/s, 20 Gb/s, or even 50 Gb/s, the ARM CPU spends most of its time handling interrupts, stripping headers, and copying data. This overhead is the "CPU Tax". The CPU Tax of High-Bandwidth Acquisition In software-based acquisition, every incoming packet triggers a CPU action. When millions of packets per second arrive, CPU utilization can easily reach 100% per core. This leaves little headroom for inference, application logic, PLC messaging, or compression tasks. Multi-camera setups make this problem even worse and often cause dropped frames or instability. Multi Camera Scale: FantoVision FPGA offload maintains a substantially lower and more predictable CPU-load profile as camera count and aggregate bandwidth increase. Latency and Synchronization Problems Industrial imaging requires deterministic latency. Software-based acquisition and non-deterministic operating-system scheduling can introduce variable latency and jitter. This jitter disrupts multi-camera synchronization, breaks high-speed inspection pipelines, and prevents precise timing between image capture, PLCs, and robotic motion. Pipeline Latency: FPGA-based parallel processing reduces processing latency compared with traditional serial CPU processing. Frame Stability: FantoVision supports continuous acquisition with zero frame loss within supported high-bandwidth configurations. Crucially, when the CPU is overwhelmed by jitter and interrupts, frames start to drop. This data loss is unacceptable in medical, defense, or high-speed inspection applications. Thermal Implications Consequently, running the CPU at high load increases thermal output. When acquisition overhead consumes more of the system’s thermal and power budget, fewer resources remain available for sustained AI processing, increasing the risk of thermal throttling under demanding workloads. The Solution: Heterogeneous Computing in an Edge AI Vision System Each FantoVision model integrates a NVIDIA Jetson Orin NX with an Altera Arria 10 FPGA, forming a heterogeneous edge AI vision system that splits responsibilities between GPU, CPU, and FPGA. The FPGA is not a passive peripheral but a Smart I/O Engine. Connecting High-Bandwidth Cameras to NVIDIA Jetson for Edge AI FantoVision integrates high-bandwidth machine vision cameras with NVIDIA Jetson through an FPGA-based acquisition path. The FPGA handles the camera interface, protocol processing, timing, and image transfer, reducing the acquisition workload on the Jetson CPU. This leaves more Jetson resources available for AI inference and application processing. Optimized Acquisition Path for Edge AI Vision and Minimal CPU Load The FPGA terminates the camera protocol, manages timing, validates data, and performs DMA transfers directly into Jetson memory that is immediately accessible by the GPU. The CPU is only notified when a complete frame is ready. This eliminates software packet handling and reduces CPU acquisition load to below 25%, even under sustained high throughput. The result is a cooler CPU, more stable system behavior, and significantly more thermal headroom for edge AI vision inference. AI Headroom: FantoVision FPGA offload reduces CPU acquisition overhead, leaving more Jetson computing and thermal resources available for AI algorithms. FPGA-Based Pre-Processing & Streaming The FPGA can offload ISP and other pixel-intensive operations, reducing Jetson CPU load and ensuring deterministic real-time performance. Capabilities include: Image Processing: Debayering, Non-Uniformity Correction (NUC), Bad Pixel Replacement (BPR), White Balance, Gamma Correction, HDR correction and dynamic luminance balancing. RTSP Output: The system supports Real-Time Streaming Protocol (RTSP) output, enabling low-latency video streaming to remote clients or control centers, ideal for drones and security applications. Data Optimization: ROI cropping, scaling, and compression including JPEG, Lossless, and Quality+. Gidel's Compression Savings: Gidel’s real-time compression technologies significantly reduce bandwidth and storage requirements, with adjustable JPEG ratios to balance quality and size. The Gidel Architecture Advantage Standard Jetson System vs. Gidel FantoVision Edge AI Vision System Feature Standard Jetson System Gidel FantoVision System Supported Interfaces USB, MIPI, Standard GigE CoaXPress 2. 1, 10 GigE Vision, Camera Link (Deca) Processing Resources Jetson only Jetson (AI) + FPGA (ISP and pre-processing) Acquisition CPU Load High, often > 60% per core Low, typically < 25% Streaming CPU-heavy encoding Optimized RTSP Out Latency Consistency OS dependent, variable jitter Hardware-driven, deterministic timing High-Bandwidth Ingestion Limited by standard interfaces and CPU load Optimized for high-speed cameras Swipe horizontally to view all columns → CPU utilization depends on camera configuration, bandwidth, packet rate, software stack, and workload. Values shown reflect representative Gidel test configurations. Three New Dedicated Edge AI Vision Systems These models bring interface-specific optimization to developers who require peak performance, reliability, and determinism in their Machine Vision Solutions. The NVIDIA CXP System: FantoVision40-CXP12 Target Applications: High-speed inspection, defense, volumetric capture, drones, sports analytics, medical imaging... Performance: Quad CXP-12 links, delivering up to 50 Gb/s bandwidth. FPGA Integration: Built-in CoaXPress 2. 1 frame grabber tightly integrated with the FPGA. Power: Supports PoCXP (Power over CoaXPress) with up to 13W per cable, simplifying cabling and power in weight-sensitive platforms... Connectivity: Micro-BNC connectors for compact, secure locking in high-vibration environments. Ideal For: ultra-fast area scan sensors and line-scan cameras. The NVIDIA 10 GigE Vision System: FantoVision20-GigE Target Applications: Intelligent Traffic Systems (ITS), stadium security, Military, surveillance, UAV imaging, and Aerial Inspection... Performance: Dual independent 10 GigE Vision ports (SFP+ or RJ45), supporting up to 20 Gb/s total bandwidth. Offload Engine: Full FPGA-based UDP and GVSP offload engine for parsing, error checking, and resend handling. Stability: Eliminates "interrupt storms" that typically overload embedded CPUs with high-bandwidth Ethernet. Versatility: Supports multi-camera aggregation or single high-bandwidth dual-link cameras. The NVIDIA Camera Link System: FantoVision20-CL Target Applications: Legacy modernization, line scan inspection, medical imaging, military & defense... Compatibility: Supports Base, Medium, Full, and 80-bit Deca Camera Link configurations. Dual Base: Unique Dual Base mode allows for the connection of two independent Camera Link Base cameras. Determinism: Provides the rock-solid triggering accuracy required for long-established production lines. Retrofit: Ideal for replacing large PC-based vision systems with compact, AI-native edge computing. FantoVision Model Specifications Overview Model FantoVision40-CXP12 FantoVision20-GigE FantoVision20-CL Primary Interface CoaXPress 2. 1 (4 × CXP-12) 10 GigE Vision (2 × 10 GigE) Camera Link Max Bandwidth 50 Gb/s 20 Gb/s 6. 8 Gb/s (Deca) Configuration Quad-link CXP-12 Dual port, SFP+ or RJ45 Deca, Full, Medium, Dual Base Power Over Cable Yes, PoCXP No No Connector Type Micro-BNC SFP+ or RJ45 SDR or MDR IP Rating IP51 IP53 IP53 Swipe horizontally to view all columns → Engineers comparing camera interfaces can also review Gidel’s guides to CoaXPress cameras, GigE Vision cameras, and Camera Link cameras. The guides cover bandwidth, connectivity, synchronization, cabling, and acquisition considerations. Compact, Rugged, and Built for the Extremes The FantoVision family is not just about electronic performance; it is engineered for physical resilience in the harshest environments. SWaP-C Optimized for Embedded Vision Dimensions: 134 × 90 × 60 mm Weight: 750 g With high-bandwidth camera acquisition, FPGA processing, and NVIDIA Jetson computing integrated into a 134 × 90 × 60 mm chassis, Gidel enables high-performance Edge AI Vision on payload-sensitive platforms such as drones and robotics, where size, weight, and power are critical. Industrial-Grade Ruggedization Unlike standard commercial electronics, the FantoVision systems are built to withstand the rigors of industrial and outdoor deployment: IP Ratings: FantoVision20 (GigE/CL): Rated IP53 (Protected against dust and spraying water). FantoVision40-CXP12: Rated IP51 (Protected against dust and vertically falling drops). Vibration & Shock: The reinforced chassis and compact mechanical design support reliable operation in vibration-prone environments. The system has been tested and deployed on UAV and drone platforms, as well as on moving machinery and AGVs. Industrial Temperature: The FantoVision systems support industrial operation across a wide temperature range, with configurations available for −25 °C to +65 °C case temperature, supporting deployment in demanding outdoor, mobile, and industrial environments. SWaP Analysis: A comparison of Size, Weight, Power (SWaP), and Performance. FantoVision combines compact dimensions, ruggedized construction, and high AI processing performance in an architecture designed for embedded and mobile deployment. Conclusion: A New Standard for Edge AI Vision Architecture The expanded FantoVision family marks an inflection point for Edge AI Vision and next-generation edge vision AI architectures. It acknowledges that different industries require specialized pipelines and that no single interface can serve all high-end applications. Whether the goal is 50 Gb/s volumetric acquisition on a drone, long-distance 10 GigE Vision streaming, or deterministic Camera Link timing, Gidel now provides targeted systems that preserve Jetson computing and thermal headroom, prevent CPU overload, and keep more of the available AI performance focused on inference and application processing. FantoVision breaks through the Jetson I/O Wall, enabling developers to transform high-bandwidth image data into real-time intelligence at the edge. © 2025 Gidel Ltd. All rights reserved. - Published: 2025-11-27 - Modified: 2026-08-31 - URL: https://gidel.com/meet-gidel-at-vision-and-ai-2025/ - Categories: Events - Tags: Embedded Vision, High-Resolution Imaging, Aerial Imaging, Machine Vision, FPGA Processing, Image Acquisition, Edge AI, GigE Vision Frame Grabbers, FPGA Compression, High-Speed Imaging, NVIDIA Jetson, Altera FPGA, Vision & AI 2025 At Vision & AI 2025, Gidel demonstrated FantoVision20-GigE with real-time 10 GigE Vision acquisition, HDR, and FPGA compression, together with SkyBoost high-resolution image acceleration. See how Gidel FPGA platforms reduce CPU/GPU workload across both Edge AI and post-processing workflows. Vision & AI 2025: Gidel Demonstrated FPGA Edge AI & Ultra-Fast High-Resolution Processing At Vision & AI 2025, Gidel demonstrated two FPGA-based imaging workflows covering real-time Edge AI vision and ultra-fast high-resolution post-processing. The demonstrations featured FantoVision20-GigE with 10 GigE Vision acquisition, real-time HDR, and compression, together with SkyBoost for accelerating very large image-processing workloads. FantoVision20-GigE: Real-Time FPGA Edge AI Vision FantoVision20-GigE: NVIDIA Jetson + FPGA Edge AI Vision System The live demonstration featured FantoVision20-GigE, combining NVIDIA Jetson Orin NX with FPGA-based 10 GigE Vision acquisition and real-time image processing. The FPGA handled deterministic image acquisition, real-time HDR, image enhancement, and Quality+ Compression before transferring the processed image data to the Jetson for AI workloads. By moving these pixel-intensive operations to the FPGA, the system reduced acquisition and image-processing overhead on the Jetson. This left more CPU/GPU resources available for detection, tracking, classification, and application processing. Engineers evaluating GigE Vision camera selection can also review Gidel’s guide to GigE Vision cameras to compare bandwidth, connectivity, cabling, synchronization, and acquisition requirements. SkyBoost: Ultra-Fast High-Resolution FPGA Processing SkyBoost: High-Resolution RAW-to-JPEG Imaging Acceleration The second demonstration featured SkyBoost, Gidel’s FPGA accelerator for high-resolution image-processing workflows. In the demonstrated workflow, SkyBoost reduced processing time from more than 20 seconds per image to more than two images per second. This dramatically accelerated post-processing workflows that could otherwise require many hours or even days. Unlike the real-time FantoVision acquisition architecture, SkyBoost accelerated large image datasets inside a host workstation or server. This architecture supports inspection, aerial imaging, mapping, photogrammetry, analysis, and other high-resolution imaging workflows. For a deeper look at this workflow, see Gidel’s article on aerial photogrammetry acceleration with SkyBoost. FPGA Processing Across Real-Time and Post-Processing Workflows The two Vision & AI 2025 demonstrations represented complementary stages of the imaging workflow. FantoVision20-GigE demonstrated FPGA processing directly during image acquisition, including camera interfacing, HDR, compression, and data preparation before NVIDIA Jetson AI processing. SkyBoost demonstrated FPGA acceleration after acquisition, processing very large image datasets inside a host workstation or server. Together, these architectures show how FPGA processing can reduce CPU/GPU bottlenecks, improve deterministic performance, and accelerate imaging workloads across both real-time and offline applications. Applications for FPGA Edge AI and High-Resolution Processing The technologies demonstrated at Vision & AI 2025 support demanding imaging applications including: Industrial automation and inspection Embedded Edge AI High-speed machine vision Outdoor and rugged imaging Aerial imaging and mapping Multi-camera imaging High-resolution image processing Robotics and autonomous systems Explore Gidel FPGA Imaging Solutions FantoVision Edge AI Systems SkyBoost High-Resolution Imaging Acceleration Real-Time HDR IP Quality+ Compression Vision & AI 2025 Event Details Tuesday, December 2, 2025 Pavilion 10, EXPO Tel Aviv Official event page: Vision & AI 2025 - Published: 2025-11-16 - Modified: 2026-08-31 - URL: https://gidel.com/meeting-the-challenges-of-high-resolution-outdoor-imaging/ - Categories: Technical Articles - Tags: Embedded Vision, High-Resolution Imaging, UAV, Aerial Imaging, FPGA Processing, Image Acquisition, Edge AI, GigE Vision Frame Grabbers, FPGA Compression High-resolution outdoor imaging faces critical challenges: extreme lighting, massive data streams, and strict SWaP limits. Discover how the partnership between Gidel and illunis solves these hurdles by combining High-Resolution Global Shutter cameras with FantoVision’s real-time FPGA compression and HDR—reducing mission data by 90% while delivering zero-loss image quality. Why High-Resolution Outdoor Imaging Is So Demanding High-resolution outdoor imaging combines several difficult engineering challenges: extreme lighting, platform motion, massive sensor data rates, storage limitations, and strict SWaP constraints. Harsh sunlight, deep shadows, glare, and rapid changes in weather can disrupt image consistency, while airborne vibration and high-resolution sensors add further demands on acquisition and processing. Key Challenges in High-Resolution Outdoor Imaging Handling extreme and inconsistent lighting conditions. Managing motion and vibration that cause image blur or distortion. Maintaining high optical precision for superior image resolution. Capturing and processing massive high-bandwidth data streams. Delivering real-time results without delays. Recording for extended durations without exhausting storage. Staying within strict SWaP limits (size, weight, and power). Efficiently offloading and processing data post-capture. Each of these hurdles is significant on its own. Combine them, and you get a serious engineering challenge. Why Standard Solutions Fall Short Most off-the-shelf systems—pairing a high-resolution camera with a standard recorder or PC—work fine in controlled environments. But outdoors, their weaknesses quickly show: limited bandwidth, rigid architectures, restricted storage, and bulky, power-hungry designs can’t keep up with modern mission demands. That gap is what motivated us to rethink how imaging systems can work together more efficiently. A Partnership Built for Real-World Demands illunis and Gidel have partnered to deliver a cost-effective, high-performance solution that’s flexible, modular, and ready for high-resolution imaging, high-bandwidth outdoor applications. The synergy between the two technologies is what makes this collaboration powerful. illunis contributes decades of expertise in ultra-high-resolution cameras (51–250 MP) featuring global shutter sensors that eliminate distortion and provide consistent results, even in motion. These cameras are rugged, lightweight, power-efficient, and built for customization—perfect for outdoor deployments. illunis also offers a range of 35 mm to large-format lens solutions and active Canon EF and RF lens mounts with electronic focus, aperture, and stabilization control, including power zoom RF support. Gidel provides FPGA-based imaging platforms that handle real-time acquisition, preprocessing, and compression of massive data streams. With features such as HDR, white balance, dynamic luminance balance and AI-assisted image processing, Gidel’s systems manage bandwidth efficiently and can extend recording capacity by up to 10×. Compact edge computers, like the FantoVision20, are engineered for low-SWaP environments where efficiency is mission-critical. Together, this partnership bridges the gap between raw sensor performance and field-deployable imaging systems. A Real-World Example: 103 MP Aerial Infrastructure Monitoring Imagine an aerial inspection mission to monitor power lines using the illunis EMC2-103MP Global Shutter CMOS camera paired with the Gidel FantoVision20 edge computer. The Application Demands Resolution & Frame Rate: The EMC2-103MP delivers 103 MP (11,276 × 9,200) images at 7. 0 fps over 10GigE, outputting 12-bit precision. Each frame is approximately 155 MB, generating a continuous 1. 09 GB/s (~8. 7 Gb/s) data stream. Mission Duration: A 3-hour flight at 7. 0 fps would yield nearly 12 TB of uncompressed data. Motion Reliability: The global shutter design ensures distortion-free capture under UAV vibration or turbulence. SWaP Efficiency: With a 440 g body and ~7 W power draw, the EMC2-103MP is lightweight and power-efficient, ideal for airborne payloads. Turnaround Speed: Post-mission data offload must be fast to minimize downtime between flights. How illunis and Gidel Solve It The Camera – illunis EMC2-103MP Global Shutter CMOS 103 MP global shutter CMOS sensor for ultra-detailed, distortion-free imaging. 3. 2 µm pixel pitch balances resolution and light sensitivity. 10GigE interface for high-speed, long-distance data transmission. 440 g weight and low power (~7 W) ensure easy UAV integration. RF Lens Controller supports aperture, focus, and zoom control for Canon RF lenses. The Gidel system can acquire directly from high-resolution GigE Vision cameras, supporting high-bandwidth imaging applications that require deterministic acquisition and flexible camera integration. The Processing & Recording: Gidel FantoVision20 FPGA-based frame grabber handles the 1. 09 GB/s stream with zero frame loss. Real-time preprocessing: HDR, white balance, dynamic luminance balance and filtering on-the-fly. On-the-fly 10× compression reduces mission data from ~12 TB to ~1. 2 TB while preserving full inspection quality. High-speed NVMe storage (>1 GB/s sustained) prevents bottlenecks. Compact design (~750g, ~30 W) ideal for UAV or aircraft integration. Optional Jetson Orin AI module enables in-flight defect detection and real-time analytics. Data Flow in Practice Parameter Uncompressed System With Compression (10×) Data Rate ~1. 09 GB/s ~109 MB/s 3-Hour Mission Data Volume ~12 TB ~1. 2 TB Storage Required 12× NVMe drives 1× NVMe drive Offload Time (10 GbE link) ~5 hours ~30 minutes Swipe horizontally to view all columns → The Outcome: Real-Time Processing of 100+ MP Outdoor Imagery With illunis and Gidel working together, this system transforms a challenging imaging workflow into a streamlined, deployable solution: No dropped frames or image distortion, even under demanding conditions. 10× data reduction enables long-duration missions without constant storage swaps. SWaP goals met, keeping payloads light and power efficient. Post-mission turnaround reduced from hours to under one hour. Instead of wrestling with data overload, teams gain a refined, ready-to-analyze image stream that drives faster, smarter decision-making. Looking Ahead to High-Resolution Imaging Solutions Outdoor imaging no longer means choosing between performance, cost, and practicality. By combining illunis’s high-resolution sensor and lens-control technology with Gidel’s FPGA-based real-time processing and compression platforms, integrators and developers now have a complete toolkit built for real-world field operations. It’s a partnership founded on a shared goal: to make cutting-edge imaging both technically robust and deployable, turning complex missions into achievable, efficient solutions. Planning a high-resolution outdoor imaging system? Contact Gidel to discuss camera bandwidth, FPGA-based acquisition and processing, compression, storage, and Edge AI requirements. For more information about high-resolution imaging solutions, visit www. illunis. com and www. gidel. com. © 2025 illunis, LLC. and © 2025 Gidel Ltd. All rights reserved. - Published: 2025-11-10 - Modified: 2026-08-31 - URL: https://gidel.com/meet-gidel-at-uvid-2025-uav-defense-innovation-exhibition/ - Categories: Events - Tags: Embedded Vision, High-Resolution Imaging, UAV, Aerial Imaging, FPGA Processing, Image Acquisition, ISR, Edge AI, GigE Vision Frame Grabbers, FPGA Compression, UVID 2025 At UVID 2025, Gidel demonstrated FPGA imaging for UAV, defense, and airborne systems with FantoVision20-GigE, real-time 10 GigE Vision acquisition, HDR, Quality+ Compression, and SkyBoost acceleration for high-resolution post-processing and mission workflows. UVID 2025 Gidel: FPGA Imaging for UAV & Defense Systems At UVID 2025, Gidel demonstrated FPGA-based imaging technologies for UAV, defense, and airborne applications. The demonstrations covered two complementary workflows: real-time image acquisition and processing with FantoVision20-GigE, and ultra-fast high-resolution post-processing with SkyBoost. FantoVision20-GigE: Real-Time FPGA Imaging for UAV & Defense The live demonstration featured FantoVision20-GigE, combining NVIDIA Jetson processing with FPGA-based 10 GigE Vision acquisition and real-time image processing. The FPGA handled deterministic image acquisition, HDR, image enhancement, and Quality+ Compression before transferring the processed image data to the Jetson for AI and application processing. By moving these pixel-intensive operations to the FPGA, the system reduced acquisition and image-processing overhead on the Jetson. This left more CPU/GPU resources available for detection, tracking, classification, and mission applications. The architecture is well suited to UAV, ISR, EO/IR, airborne surveillance, and rugged imaging systems that require low latency, deterministic acquisition, and efficient bandwidth usage. Engineers evaluating GigE Vision camera selection can also review Gidel’s guide to GigE Vision cameras to compare bandwidth, connectivity, cabling, synchronization, and acquisition requirements. SkyBoost: Ultra-Fast High-Resolution Processing SkyBoost demonstrated FPGA acceleration for high-resolution image-processing workflows. In the demonstrated workflow, SkyBoost reduced processing time from more than 20 seconds per image to more than two images per second. This significantly accelerates post-processing of large aerial and mission image datasets that might otherwise require many hours or even days. For UAV and defense applications, this can shorten workflows involving aerial reconnaissance, mapping, inspection, intelligence analysis, and mission reporting. For a deeper look at this workflow, see Gidel’s article on aerial photogrammetry acceleration with SkyBoost. FPGA Processing Across Real-Time and Post-Mission Workflows The two UVID 2025 demonstrations represented complementary stages of an airborne imaging workflow. FantoVision20-GigE demonstrated FPGA processing directly during acquisition, including camera interfacing, HDR, image enhancement, compression, and data preparation before NVIDIA Jetson AI processing. SkyBoost demonstrated FPGA acceleration after acquisition, processing large high-resolution image datasets inside a host workstation or server. Together, these architectures show how FPGA processing can reduce bandwidth pressure and CPU/GPU bottlenecks during a mission while also accelerating high-resolution analysis after the mission Applications for UAV, Defense & Airborne Imaging The technologies demonstrated at UVID 2025 support demanding imaging applications including: ISR and EO/IR imaging UAV and airborne payloads Aerial surveillance and reconnaissance High-resolution aerial imaging Recording with constrained data links Real-time image enhancement Edge AI detection and classification Post-mission image processing and analysis Rugged and low-SWaP imaging systems Explore Gidel FPGA Imaging Solutions FantoVision Edge AI Systems SkyBoost High-Resolution Imaging Acceleration Real-Time HDR Quality+ Compression UVID 2025 Event Details Wednesday, November 26, 2025 Pavilion 1, EXPO Tel Aviv Official event page: UVID DroneTech - Published: 2025-11-02 - Modified: 2026-08-31 - URL: https://gidel.com/meet-gidel-at-the-military-aviation-exhibition-fpga-imaging-solutions/ - Categories: Events - Tags: Embedded Vision, UAV, Aerial Imaging, FPGA Processing, Image Acquisition, ISR, CoaXPress Frame Grabbers, Edge AI, Camera Link Frame Grabbers, FPGA Compression, High-Speed Imaging, Military & Aviation 2025 At the Military & Aviation Exhibition 2025, Gidel demonstrated FPGA-based airborne imaging systems for UAV, ISR, EO/IR, and tactical applications. FantoVision20-CL and FantoVision40-CXP12 combine deterministic camera acquisition, real-time HDR, compression, and NVIDIA Jetson processing in compact low-SWaP platforms. FPGA Airborne Imaging Systems for Military & Aviation Applications At the Military & Aviation Exhibition 2025, Gidel demonstrated FPGA-based airborne imaging systems for UAV, ISR, EO/IR, and tactical applications. The exhibition featured FantoVision20-CL and FantoVision40-CXP12, combining deterministic camera acquisition, real-time FPGA processing, compression, and NVIDIA Jetson computing in compact low-SWaP platforms. FantoVision20-CL: Camera Link for Airborne & Tactical Systems FantoVision20-CL combines NVIDIA Jetson processing with FPGA-based Camera Link acquisition and real-time image processing. The system supports Camera Link Base, Medium, Full, 80-bit Deca, and Dual Base configurations, making it suitable for airborne and tactical systems that continue to rely on deterministic Camera Link cameras while requiring modern embedded processing. The FPGA can handle deterministic image acquisition, HDR, image enhancement, compression, and data preparation before transferring the processed image data to the Jetson for AI and application processing. By moving these pixel-intensive operations to the FPGA, the architecture reduces acquisition and image-processing overhead on the Jetson while maintaining predictable low-latency performance. Engineers evaluating Camera Link camera selection can also review Gidel’s guide to Camera Link cameras to compare supported configurations, cabling, synchronization, and acquisition requirements. FantoVision40-CXP12: High-Bandwidth CoaXPress for Airborne & Tactical Systems FantoVision40-CXP12 combines NVIDIA Jetson processing with FPGA-based CoaXPress-12 acquisition and real-time image processing. The system supports up to four CXP-12 links with PoCXP, providing up to 50 Gb/s aggregate interface bandwidth for high-resolution and high-frame-rate imaging systems. For airborne, UAV, and tactical applications, this architecture supports deterministic high-bandwidth acquisition while reducing the processing burden placed on the Jetson CPU/GPU. Engineers evaluating high-bandwidth camera options can also review Gidel’s guide to CoaXPress cameras. Why FPGA Processing Matters in Airborne Imaging Systems Airborne imaging platforms must process large camera data streams while operating within strict size, weight, power, bandwidth, and latency constraints. Placing FPGA processing directly in the acquisition path enables time-critical and pixel-intensive operations to be performed before image data reaches the CPU or GPU. Gidel’s FPGA-based architecture can support: Deterministic camera acquisition Real-time HDR and image enhancement Image compression Filtering and preprocessing Protocol handling Low-latency data transfer Reduced CPU/GPU acquisition overhead More efficient use of storage and data-link bandwidth This architecture provides a predictable processing path for mission-critical imaging while preserving Jetson resources for AI inference and application-level processing. Camera Link and CoaXPress for Different Airborne Imaging Requirements The two FantoVision systems demonstrated at the exhibition address different camera-interface requirements. FantoVision20-CL supports established Camera Link cameras and is particularly relevant for systems where deterministic acquisition, compatibility with existing sensors, and retrofit capability are important. FantoVision40-CXP12 addresses newer high-bandwidth architectures requiring CoaXPress-12 connectivity, PoCXP, higher data rates, and compact multi-camera acquisition. Both platforms combine FPGA-based acquisition and processing with NVIDIA Jetson computing, allowing system developers to select the camera interface that best matches their sensor, bandwidth, and mission requirements. Low-SWaP Processing for Airborne and Tactical Platforms Size, weight, and power are critical constraints in UAV, airborne, and tactical imaging systems. Gidel’s FantoVision architecture integrates camera acquisition, FPGA processing, NVIDIA Jetson computing, and optional recording in a compact embedded system, reducing the need for a separate frame grabber and large host computer. This approach is particularly useful for imaging payloads deployed close to the sensor, where deterministic performance and high processing capability must be achieved within limited mechanical and power budgets. Applications for Airborne Imaging Systems The technologies demonstrated at the Military & Aviation Exhibition 2025 support applications including: ISR and EO/IR imaging UAV and airborne payloads Aerial surveillance and reconnaissance Tactical imaging and recording High-resolution airborne imaging Multi-camera sensor systems Real-time image enhancement Edge AI detection, tracking, and classification Recording under constrained data-link bandwidth Rugged and low-SWaP imaging platforms Explore Gidel FPGA Imaging Solutions FantoVision20-CL FantoVision40-CXP12 Real-Time HDR Quality+ Compression Gidel PCIe Frame Grabbers Military & Aviation Exhibition 2025 Event Details Monday, November 10, 2025 Pavilion 10, EXPO Tel Aviv - Published: 2025-11-02 - Modified: 2026-08-31 - URL: https://gidel.com/low-latency-system-fpga/ - Categories: Technical Articles - Tags: Embedded Vision, High-Resolution Imaging, Machine Vision, FPGA Processing, Image Acquisition, Edge AI, FPGA Compression, High-Speed Imaging, Low-Latency Vision Systems Low latency vision systems must increase throughput without sacrificing responsiveness, determinism, or power efficiency. See how FPGA acceleration and hybrid FPGA, CPU, GPU, and AI architectures process high-bandwidth imaging workloads in real time while minimizing added processing latency. Understanding Performance in Low Latency Vision Systems In modern vision and AI applications, performance in low latency vision systems isn’t only about raw speed. It requires a balance between throughput, latency, accuracy, power efficiency, and time-to-market. Higher resolutions, faster frame rates, and multi-camera configurations significantly increase data loads. However, improving one parameter (such as throughput) can often compromise another, like latency or power. The true challenge lies in boosting overall performance while maintaining responsiveness, determinism, and power efficiency. For engineers optimizing throughput and responsiveness in high-speed vision systems, Gidel’s PCIe Frame Grabbers provide FPGA-based acquisition and processing platforms for many of the architectures discussed below. What Low Latency Means in Real-World Systems The importance of latency is easy to see in algorithmic trading, where milliseconds can determine the outcome of a transaction. In machine vision, autonomous systems, medical imaging, and real-time AI, the consequences are different, but the architectural principle is the same: processing more data is useful only if the system can maintain the required response time. In algorithmic trading, a millisecond can make or break a deal; it is a clear reminder that system performance is about much more than speed. The Performance Dilemma in Low Latency Systems Every vision system faces a fundamental engineering trade-off: the more data you process, the harder it becomes to maintain real-time responsiveness. This balance between computational power and latency defines the limits of many imaging systems, from autonomous vehicles to medical devices. Instead of simply adding more processing power, a more effective approach is to rethink the system architecture, designing a pipeline where each component contributes to higher performance without unnecessarily increasing response time. That’s where hybrid computing comes into play. FPGA Low Latency Acceleration with Hybrid Computing Gidel’s hybrid computing architecture combines FPGA, CPU, GPU, and AI engines, allowing each to do what it does best. Task Type Optimal Processor Key Advantage Control logic, decision branches, adaptive algorithms CPU Flexibility for software-driven and adaptive processing Highly parallel numerical or AI workloads GPU / AI Engine High compute throughput for parallel workloads Streaming and repetitive pixel processing, such as histograms, gamma, and compression FPGA Parallel processing, deterministic low latency, and high efficiency This division enables the system to process more data in parallel, increasing throughput while minimizing additional processing latency. In edge deployments that combine FPGA acceleration with embedded AI, Gidel’s FantoVision systems integrate NVIDIA Jetson computing with FPGA-based acquisition and processing in compact, power-efficient platforms. Example: Hybrid Histogram Processing A practical example of this hybrid approach is histogram-based image analysis. The FPGA performs repetitive pixel-level processing, incrementing pixel counts and building the histogram table. The CPU analyzes the completed table, detecting patterns, peaks, or applying corrections. In a hybrid architecture, the FPGA handles repetitive pixel processing and histogram generation, while the CPU analyzes the resulting histogram. Each processor is assigned the type of workload it handles most effectively. Why FPGA Processing Provides Deterministic Low Latency FPGA pipelines implement processing functions as dedicated parallel hardware paths rather than relying on general-purpose software scheduling. Once the pipeline is filled, pixels can move through processing stages continuously with predictable timing. This allows functions such as acquisition, protocol handling, filtering, HDR, image enhancement, and compression to operate concurrently without waiting for general-purpose CPU/GPU scheduling. The benefit is not simply higher throughput. It is predictable processing latency that can be designed and validated as part of the system architecture. Real-Time FPGA Image Processing Without Added Latency Imaging workloads can be offloaded to the FPGA for high-throughput, deterministic processing using GIL - Gidel Imaging Libraries. When these functions are implemented directly in the streaming acquisition pipeline, they can be executed without introducing additional frame-level processing stages on the CPU or GPU. One practical demonstration of this concept is Gidel’s HDR IP for real-time high dynamic range image processing. Many conventional HDR approaches combine multiple exposures, which can reduce effective frame rate and introduce additional latency or motion-related artifacts. Gidel’s FPGA-based processing pipeline addresses this challenge by performing multiple image-processing functions within the streaming FPGA pipeline: Single-frame HDR processing Gamma correction, white balance and dynamic luminance balance Optional edge enhancement to improve feature visibility for downstream detection algorithms On-FPGA JPEG compression - Explore Gidel’s Image Compression IPs to learn more about real-time FPGA-based compression and data reduction technologies. Processing speeds exceeding 1 gigapixel per second The result is improved image quality at real-time processing rates, with latency determined primarily by the defined FPGA pipeline rather than by additional frame-based software processing. To see how this works in practice, explore Gidel's HDR IP, which performs single-frame HDR with real-time gamma correction, white balance, dynamic luminance balance, and enhancement directly on the FPGA. Real-Time FPGA Processing of a >100 MP Image Beyond Raw Speed: What Defines Performance in Low Latency Vision Systems Reducing Development Cycles True system performance isn’t limited to runtime metrics. Long development and validation loops can slow innovation just as much as inefficient code. Gidel’s modular FPGA environment, combined with tools such as Camera Simulators, can shorten development and validation cycles from early integration through system testing. Shorter development time means products reach the market sooner, an often overlooked but critical part of overall performance. Power Efficiency as a Competitive Advantage As data rates and AI workloads grow, power efficiency becomes a defining factor in performance. FPGAs implement selected processing functions as dedicated parallel hardware paths, which can provide high computational efficiency for repetitive and streaming workloads. For suitable workloads, this can reduce processing overhead and improve performance per watt while maintaining deterministic real-time operation. Power efficiency doesn’t just reduce cost; it can support reliability and predictable operation, especially in mission-critical or embedded environments. Scalability for Future Demands Performance requirements rarely stay constant. Systems that can scale in resolution, frame rate, or algorithmic complexity maintain their value over time. Gidel’s modular hybrid architecture allows FPGA processing resources to be added alongside CPU or GPU systems while preserving much of the existing software architecture. This flexibility helps companies keep up with evolving demands in vision, robotics, and AI while maintaining control over latency and system performance. Building Higher-Performance Low Latency Vision Systems Improving performance while controlling latency is not simply a matter of adding more compute. It requires assigning each workload to the processing architecture best suited to it. By combining FPGA acceleration, modular design, and hybrid computing, engineers can improve several important system-level metrics: Higher throughput while maintaining real-time operation Deterministic low latency for defined processing pipelines Power efficiency and scalability Reduced time-to-market Gidel’s acquisition platforms include PCIe Frame Grabbers, Mini FPGA Modules, FantoVision Edge AI Systems, and Camera Simulators, providing the building blocks to create faster, smarter, and more efficient imaging and vision systems. Ready to evaluate where FPGA acceleration can improve your vision system? Request a demo or contact our team to discuss acquisition, FPGA processing, and hybrid computing requirements for your next-generation vision platform. © 2025 Gidel Ltd. All rights reserved. - Published: 2025-05-23 - Modified: 2026-08-31 - URL: https://gidel.com/defense-solutions-exhibition/ - Categories: Events - Tags: Embedded Vision, UAV, FPGA Processing, Image Acquisition, ISR, Edge AI, GigE Vision Frame Grabbers, FPGA Compression, High-Speed Imaging, Defense Solutions 2025 At the Defense Solutions Exhibition 2025, Gidel demonstrated real-time FPGA imaging for defense using FantoVision20-GigE, with 10 GigE Vision acquisition, single-frame HDR, Quality+ Compression, and deterministic low-latency processing. Real-Time FPGA Imaging for Defense Applications At the Defense Solutions Exhibition 2025, Gidel demonstrated FPGA-based imaging technologies for defense, UAV, ISR, and high-performance vision applications. The live demonstration focused on real-time image acquisition and processing with FantoVision20-GigE, combining 10 GigE Vision, FPGA-based image enhancement, compression, and NVIDIA Jetson AI processing in a compact Edge AI platform. FantoVision20-GigE: Real-Time FPGA Imaging for Defense The live demonstration featured FantoVision20-GigE, combining NVIDIA Jetson processing with FPGA-based 10 GigE Vision acquisition and real-time image processing. The FPGA handled deterministic image acquisition, HDR, image enhancement, and Quality+ Compression before transferring the processed image data to the Jetson for AI and application processing. By moving these pixel-intensive operations to the FPGA, the system reduced acquisition and image-processing overhead on the Jetson, leaving more CPU/GPU resources available for detection, tracking, classification, and mission applications. The architecture is well suited to defense imaging, UAV, ISR, EO/IR, airborne surveillance, and rugged vision systems that require low latency, deterministic acquisition, and efficient bandwidth usage. Engineers evaluating GigE Vision camera selection can also review Gidel’s guide to GigE Vision cameras to compare bandwidth, connectivity, cabling, synchronization, and acquisition requirements. FPGA Processing for Real-Time Defense Imaging The Defense Solutions Exhibition 2025 demonstration showed how FPGA processing can be integrated directly into the image-acquisition pipeline. Instead of transferring raw camera data to the NVIDIA Jetson and relying on the CPU/GPU for every processing stage, the FPGA can handle acquisition, HDR, image enhancement, compression, and data preparation before the image reaches the Jetson. This architecture reduces processing overhead and helps maintain predictable low-latency operation while preserving more Jetson computing resources for AI inference and application processing. For defense, UAV, and ISR systems, this can be particularly valuable in applications where high-bandwidth sensors, constrained data links, low-SWaP platforms, and deterministic real-time performance must be combined in a compact system. Applications for Defense, UAV & ISR Vision Systems The technologies demonstrated at the Defense Solutions Exhibition 2025 support demanding imaging applications including: ISR and EO/IR imaging UAV and airborne payloads Aerial surveillance and reconnaissance Real-time image enhancement Edge AI detection, tracking, and classification 10 GigE Vision acquisition for high-bandwidth imaging Image compression for constrained data links and storage Rugged and low-SWaP imaging systems Mission and tactical vision applications Explore Gidel FPGA Imaging Solutions FantoVision Edge AI Systems Real-Time HDR Quality+ Compression Gidel PCIe Frame Grabbers Defense Solutions Exhibition 2025 Event Details Tuesday, June 17, 2025 Daniel Hotel, Herzliya, Israel - Published: 2025-05-06 - Modified: 2026-09-07 - URL: https://gidel.com/chipex2025-exhibition/ - Categories: Events - Tags: Embedded Vision, Machine Vision, FPGA Processing, Image Acquisition, CoaXPress Frame Grabbers, Edge AI, GigE Vision Frame Grabbers, Camera Link Frame Grabbers, FPGA Compression, High-Speed Imaging, ChipEx 2025 At the ChipEx 2025 Exhibition, Gidel demonstrated FantoVision20-GigE with real-time 10 GigE Vision acquisition, single-frame HDR, Quality+ Compression, and deterministic FPGA processing for high-performance imaging and Edge AI. ChipEx 2025: Gidel Demonstrated Real-Time FPGA Imaging and Edge AI At the ChipEx 2025 Exhibition, Gidel demonstrated FPGA-based imaging technologies for high-performance vision, embedded AI, and real-time image-processing applications. The live demonstration featured FantoVision20-GigE, combining NVIDIA Jetson processing with FPGA-based 10 GigE Vision acquisition and real-time image processing in a compact Edge AI platform. FantoVision20-GigE: Real-Time 10 GigE Vision Demo The FPGA handled deterministic image acquisition, HDR, image enhancement, and Quality+ Compression before transferring the processed image data to the Jetson for AI and application processing. By moving these pixel-intensive operations to the FPGA, the system reduced acquisition and image-processing overhead on the Jetson, leaving more CPU/GPU resources available for AI inference and application processing. Key capabilities demonstrated at ChipEx 2025 included: Real-time 10 GigE Vision acquisition for high-bandwidth imaging Single-frame HDR processing to improve image detail across challenging lighting conditions Quality+ Compression for substantial data reduction while maintaining high image quality Deterministic FPGA processing for predictable real-time operation Sub-frame processing latency through FPGA-based acquisition and inline image processing Engineers evaluating GigE Vision camera selection can also review Gidel’s guide to GigE Vision cameras to compare bandwidth, connectivity, cabling, synchronization, and acquisition requirements. FPGA Processing for High-Performance Vision Systems The ChipEx 2025 demonstration showed how FPGA processing can be integrated directly into the image-acquisition pipeline. Instead of transferring raw camera data to the NVIDIA Jetson and relying on the CPU/GPU for every processing stage, the FPGA can handle acquisition, protocol processing, HDR, image enhancement, compression, and data preparation before the image reaches the Jetson. This architecture helps maintain predictable low-latency operation while preserving more Jetson computing resources for AI inference and application processing. For semiconductor and industrial vision systems, embedded AI, and other high-performance imaging applications, this approach can be particularly valuable when high-resolution sensors, high data rates, deterministic acquisition, and real-time processing must operate together. High-Bandwidth FPGA Imaging Interfaces Gidel’s FPGA imaging platforms support multiple camera interfaces for high-performance acquisition and processing: GigE Vision frame grabbers for flexible high-bandwidth Ethernet-based acquisition CoaXPress frame grabbers for very high-bandwidth acquisition, including CXP-12 Camera Link frame grabber for deterministic acquisition with established industrial camera interfaces These FPGA-based platforms can combine camera acquisition with real-time processing, image enhancement, compression, and data preparation within the same processing pipeline. Explore Gidel FPGA Imaging Solutions FantoVision Edge AI Systems Real-Time HDR Quality+ Compression Gidel PCIe Frame Grabbers ChipEx 2025 Event Details Tuesday, May 13, 2025 EXPO Tel Aviv ChipEx 2025 brought together semiconductor, electronics, and technology professionals to explore developments across the chip industry and related high-performance computing applications. Gidel participated with a live demonstration of FPGA-based image acquisition, real-time processing, HDR, compression, and embedded Edge AI. Official event website: ChipEX - Published: 2025-02-23 - Modified: 2026-09-07 - URL: https://gidel.com/vision-china-2025/ - Categories: Events - Tags: Embedded Vision, Machine Vision, FPGA Processing, Image Acquisition, CoaXPress Frame Grabbers, Edge AI, GigE Vision Frame Grabbers, Camera Link Frame Grabbers, FPGA Compression, High-Speed Imaging, NVIDIA Jetson, Altera FPGA, Vision China 2025 At Vision China 2025 in Shanghai, Gidel demonstrated FPGA-based machine vision technologies including FantoVision Edge AI, CoaXPress-12 acquisition, real-time HDR, Quality+ Compression, and scalable multi-camera processing. Vision China 2025: Gidel Demonstrated FPGA Machine Vision and Edge AI At Vision China 2025, Gidel demonstrated modular FPGA-based technologies for high-speed machine vision, real-time processing, Edge AI, and multi-camera acquisition. The demonstrations showed how Gidel combines FPGA-based image acquisition and processing with high-bandwidth camera interfaces and NVIDIA Jetson computing to support demanding automation, inspection, robotics, and quality-control applications. FantoVision: Compact Edge AI Vision with FPGA Acquisition Gidel presented its FantoVision Edge AI Systems, combining NVIDIA Jetson computing with FPGA-based camera acquisition and real-time image processing in compact embedded platforms. The FPGA can handle deterministic acquisition, image enhancement, HDR, compression, and data preparation before transferring processed image data to the Jetson for AI and application processing. By moving these pixel-intensive operations to the FPGA, the architecture can reduce acquisition and image-processing overhead on the Jetson, leaving more CPU/GPU resources available for inference, detection, tracking, classification, and application logic. High-Bandwidth Machine Vision Acquisition and Processing Vision China 2025 highlighted Gidel’s modular FPGA architecture for high-speed image acquisition and real-time processing. Gidel’s platforms support multiple machine vision interfaces, including: CoaXPress frame grabbers for very high-bandwidth acquisition, including CXP-12 GigE Vision frame grabbers for flexible high-bandwidth Ethernet-based imaging Camera Link frame grabbers for deterministic acquisition with established industrial camera interfaces Custom sensor and imaging interfaces for specialized system requirements Gidel’s FPGA-based architecture enables image acquisition and processing to operate within the same deterministic pipeline, supporting machine vision systems that require high throughput, low latency, and predictable timing. Engineers comparing camera interfaces can also review Gidel’s guides to CoaXPress cameras, GigE Vision cameras, and Camera Link cameras. The guides cover bandwidth, connectivity, synchronization, cabling, and acquisition considerations. Real-Time HDR and Image Compression Gidel also demonstrated FPGA-based image enhancement and data-reduction technologies. Real-Time HDR improves visibility across challenging lighting conditions while maintaining real-time processing within the FPGA pipeline. Quality+ Compression reduces image data volume while maintaining high image quality, helping reduce bandwidth and storage requirements in high-resolution and high-frame-rate imaging systems. These capabilities are particularly relevant to inspection, semiconductor, robotics, precision manufacturing, and other machine vision applications where large image volumes must be processed continuously. High-End Vision Demos at Vision China 2025 The demonstrations included: Real-time CoaXPress-12 acquisition with FPGA-based HDR and compression using Altera Arria 10 Advanced Imaging & Vision IP development for real-time processing, testing, and validation Multi-camera FPGA acquisition and processing for high-bandwidth machine vision architectures Edge AI integration combining FPGA preprocessing with NVIDIA Jetson computing Together, these demonstrations showed how FPGA processing can address bandwidth, latency, acquisition, and image-processing challenges across advanced machine vision systems. Explore Gidel Machine Vision Solutions FantoVision Edge AI Systems Quality+ Real-Time Compression Real-Time HDR IP Gidel PCIe Frame Grabbers Vision China 2025 Event Details March 26 to 28, 2025 Shanghai New International Expo Centre, SNIEC Hall W5, Booth 5417 Official event website: Vision China - Published: 2025-02-20 - Modified: 2026-09-08 - URL: https://gidel.com/join-us-at-imvc-2025-gidel/ - Categories: Events - Tags: Embedded Vision, Machine Vision, FPGA Processing, Image Acquisition, CoaXPress Frame Grabbers, Edge AI, GigE Vision Frame Grabbers, Camera Link Frame Grabbers, FPGA Compression, High-Speed Imaging, Altera FPGA, IMVC 2025 At IMVC 2025, Gidel demonstrated FPGA imaging and Edge AI technologies including real-time CoaXPress-12 acquisition, HDR, Quality+ Compression, high-bandwidth processing, and FPGA-based vision development. IMVC 2025: Gidel Demonstrated FPGA Imaging and Edge AI At IMVC 2025, Gidel demonstrated FPGA-based technologies for high-performance imaging, real-time processing, Edge AI, and machine vision applications. The demonstrations highlighted how FPGA-based acquisition and image processing work with high-bandwidth camera interfaces and AI computing. This architecture supports demanding inspection, automation, robotics, and embedded vision systems. Real-Time CoaXPress-12 Acquisition and FPGA Processing One of the live demonstrations featured the HawkEye-CXP12 with four CoaXPress-12 links and real-time FPGA-based image processing using an Altera Arria 10 FPGA. The FPGA handled deterministic image acquisition, HDR, image enhancement, and Quality+ Compression within the real-time processing pipeline. By performing these pixel-intensive functions directly on the FPGA, the architecture can reduce CPU/GPU processing overhead while maintaining predictable low-latency operation. Engineers evaluating CoaXPress camera selection can also review Gidel’s guide to CoaXPress cameras to compare bandwidth, link count, cabling, synchronization, and acquisition requirements. FPGA Imaging for High-Bandwidth Machine Vision Gidel’s FPGA platforms support demanding imaging systems that require high data rates, deterministic acquisition, and real-time processing. Supported machine vision interfaces include: CoaXPress frame grabbers for very high-bandwidth acquisition, including CXP-12 GigE Vision frame grabbers for flexible Ethernet-based high-bandwidth imaging Camera Link frame grabbers for deterministic acquisition with established industrial camera interfaces Custom sensor and imaging interfaces for specialized system requirements These FPGA-based acquisition platforms combine camera interfacing, protocol processing, synchronization, image enhancement, and compression. They can also perform data preparation within the same processing architecture. Real-Time HDR and Image Compression Gidel also demonstrated FPGA-based image enhancement and data-reduction technologies. Real-Time HDR improves visibility across challenging lighting conditions while operating within the FPGA processing pipeline. Quality+ Compression reduces image data volume while maintaining high image quality, helping reduce bandwidth and storage requirements in high-resolution and high-frame-rate imaging systems. These capabilities are particularly relevant to inspection, metrology, robotics, semiconductor, medical imaging, and other applications where large image volumes must be processed continuously. FPGA Vision Development and Validation A second demonstration highlighted Gidel’s FPGA imaging and vision IP development capabilities for real-time processing, testing, and validation. The platform enables developers to integrate custom FPGA processing pipelines alongside image acquisition, allowing algorithms and imaging functions to be implemented directly in hardware when deterministic timing, high throughput, or low latency are required. This approach supports development of advanced imaging pipelines for machine vision, Edge AI, inspection, and other high-performance vision applications. Explore Gidel Machine Vision Solutions Gidel PCIe Frame Grabbers Real-Time HDR IP Quality+ Compression FantoVision Edge AI Systems IMVC 2025 Event Details Tuesday, April 1, 2025 Pavilion 10, EXPO Tel Aviv Main Hall, Booth 7 IMVC 2025 brought together professionals from computer vision, image processing, AI, machine learning, embedded vision, robotics, medical imaging, metrology, and other related fields. Gidel participated with demonstrations of FPGA-based image acquisition, real-time processing, HDR, compression, and advanced imaging development. Official event website: IMVC 2025 - Published: 2025-01-30 - Modified: 2026-09-08 - URL: https://gidel.com/gidel-quality-plus-compression-top-innovation-2025/ - Categories: Technical Articles, Press release, Company Updates - Tags: Embedded Vision, High-Resolution Imaging, Machine Vision, FPGA Processing, Image Acquisition, Edge AI, FPGA Compression, High-Speed Imaging Gidel Quality+ Compression received inVISION Top Innovation 2025 recognition for real-time FPGA compression with 1:10+ data reduction, more than 1.2 gigapixels per second, and less than one frame of latency. Gidel Quality+ Compression Award 2025: Why the Technology Stands Out The Gidel Quality+ Compression Award 2025 recognition from inVISION highlights Gidel’s FPGA-based compression technology for high-bandwidth imaging and machine vision systems. Quality+ Compression reduces image data in real time while maintaining high image quality. Gidel designed it for imaging systems where bandwidth, storage, throughput, and latency are critical. Real-Time 1:10+ Compression While Maintaining Image Quality Quality+ Compression can deliver compression ratios of approximately 1:10+ while preserving the image information required by demanding vision applications. This makes the technology relevant to industrial inspection, semiconductor inspection, fixed-camera surveillance, high-resolution recording, scientific imaging, and other applications where large image streams must be reduced without sacrificing useful image information. More Than 1. 2 Gigapixels per Second with Sub-Frame Latency Quality+ Compression processes more than 1. 2 gigapixels per second while operating with less than one frame of latency. Because Quality+ Compression runs directly in the FPGA, it can reduce image data close to the acquisition stage. This lowers the amount of data that downstream processors, storage systems, and networks must handle. FPGA Compression for High-Bandwidth Imaging Systems Gidel integrates Quality+ Compression directly into FPGA-based acquisition and image-processing pipelines. The compression engine can operate alongside camera acquisition, image enhancement, HDR, and other FPGA processing stages. This creates a deterministic pipeline that reduces image data before it moves deeper into the system. As image resolutions, frame rates, and camera counts increase, this approach helps system designers manage larger image streams without transferring the full uncompressed workload through the entire processing chain. Quality+ Compression Supported Platforms Gidel supports Quality+ Compression across its acquisition and FPGA processing platforms, including: PCIe Frame Grabbers for high-bandwidth image acquisition and FPGA processing FantoVision Edge AI Systems for compact embedded acquisition, FPGA processing, and NVIDIA Jetson AI Mini FPGA Modules for custom embedded, OEM, and high-performance imaging systems Quality+ Compression runs in the FPGA processing pipeline before the system transfers image data to the host CPU, GPU, Jetson processor, storage system, or network. This allows the same Quality+ Compression technology to support different Gidel hardware architectures while preserving deterministic FPGA processing and low-latency operation. Why the Gidel Quality+ Compression Award 2025 Matters The Gidel Quality+ Compression Award 2025 recognition reflects a growing challenge across machine vision and high-performance imaging systems. Modern cameras continue to increase resolution, frame rate, and aggregate data throughput. This places greater pressure on PCIe bandwidth, memory, storage, networks, CPUs, GPUs, and embedded AI processors. Quality+ Compression addresses this challenge by reducing image data close to acquisition. This helps prevent unnecessary uncompressed data from consuming downstream bandwidth and storage resources. The technology is relevant to applications such as industrial inspection, defense imaging, long-duration recording, and other high-bandwidth vision systems. Learn more about Gidel Quality+ Compression: Quality+ Compression Read the inVISION recognition: inVISION Real-Time Compression Contact Gidel experts: Contact Us - Published: 2025-01-13 - Modified: 2026-09-08 - URL: https://gidel.com/2024-a-year-of-innovation-and-milestones-gidel/ - Categories: Technical Articles, Company Updates - Tags: Embedded Vision, Machine Vision, FPGA Processing, Image Acquisition, Edge AI, FPGA Compression, Aerospace & Defense Explore the Gidel 2024 Milestones, including advances in modular FPGA imaging, rugged edge computing platforms, global expansion, and more than 20 years of lifecycle support for mission-critical imaging systems. Gidel 2024 Milestones: Advancing FPGA Imaging and Edge Computing Gidel 2024 Milestones reflect a year of progress in FPGA-based imaging, modular hardware, rugged edge computing, global expansion, and long-term product support. During 2024, Gidel expanded the flexibility of its FPGA platforms, strengthened its edge-computing capabilities, and continued supporting high-performance imaging systems across industrial, defense, and other demanding applications. 1. Expanding Modular FPGA Imaging Platforms Gidel continued advancing its modular FPGA architecture, giving system developers greater flexibility to configure acquisition, processing, memory, and interface capabilities for specific imaging requirements. This modular approach supports applications that require deterministic image acquisition, real-time FPGA processing, high data throughput, and long-term hardware availability. Gidel’s modular hardware portfolio includes PCIe Frame Grabbers for high-bandwidth image acquisition and FPGA processing, as well as Mini FPGA Modules for custom embedded, OEM, and high-performance imaging systems. 2. Rugged Edge Computing for Real-Time Imaging In 2024, Gidel expanded its FantoVision Edge AI Systems with increased ruggedization and support for extended industrial operating conditions. These developments strengthened Gidel’s ability to support compact imaging and vision systems deployed in demanding environments where size, weight, power, reliability, and real-time processing are important. FantoVision combines FPGA-based image acquisition and processing with embedded NVIDIA Jetson computing. This architecture allows imaging workloads to be handled close to the sensor before data moves deeper into the system for AI and application processing. 3. Strengthening Gidel’s Global Presence Gidel continued expanding its international presence across North America, Europe, the Middle East, and Asia. During 2024, Gidel participated in major imaging, embedded technology, industrial, and defense events, including: Embedded World 2024, Nuremberg VISION 2024, Stuttgart Vision China Shanghai 2024 Military & Aviation 2024, Tel Aviv Industry 4. 0 Delegation organized by the Israeli Ministry of Economy and Industry in Italy and Germany These activities helped Gidel engage with system developers, camera manufacturers, integrators, and technology partners across global machine vision and high-performance imaging markets. 4. Long-Life Production and Lifecycle Support Long-term availability remained an important part of Gidel’s technology strategy in 2024. Gidel continued providing long-life production and more than 20 years of lifecycle support for FPGA-based imaging platforms. This commitment is particularly important for industrial, defense, scientific, and mission-critical systems that require stable hardware platforms, predictable maintenance, and long product lifecycles. Gidel 2024 Milestones Built the Foundation for 2025 Gidel 2024 Milestones established a strong foundation for continued development in FPGA imaging, Edge AI, real-time image processing, and high-bandwidth acquisition. The modular FPGA architecture, rugged edge-computing developments, global expansion, and long-life production strategy carried directly into the next generation of Gidel imaging and vision systems. Explore Gidel Image Acquisition Platforms and FPGA Processing IPs Image Acquisition Platforms PCIe Frame Grabbers FantoVision Edge AI Systems Mini FPGA Modules FPGA Processing IPs Quality+ Compression Real-Time HDR IP - Published: 2024-11-21 - Modified: 2026-09-08 - URL: https://gidel.com/military-aviation-2024/ - Categories: Events - Tags: Embedded Vision, UAV, FPGA Processing, Image Acquisition, ISR, Recording & Streaming, CoaXPress Frame Grabbers, Edge AI, GigE Vision Frame Grabbers, Camera Link Frame Grabbers, FPGA Compression, High-Speed Imaging, Aerospace & Defense, Military & Aviation 2024 At Military & Aviation 2024, Gidel demonstrated FPGA-based imaging and Edge AI technologies for defense and aerospace, including high-speed acquisition, real-time processing, Quality+ Compression, image enhancement, recording, and NVIDIA Jetson integration. Military & Aviation 2024: Gidel Demonstrated FPGA Imaging and Edge AI At Military & Aviation 2024, Gidel demonstrated FPGA-based imaging technologies for defense, aerospace, UAV, and other mission-critical vision applications. The demonstrations focused on high-speed image acquisition, deterministic FPGA processing, real-time image enhancement, compression, recording, and NVIDIA Jetson-based Edge AI processing. Real-Time FPGA Imaging for Defense and Aerospace Gidel’s FPGA-based imaging architecture supports demanding defense and aerospace systems that require high data rates, low latency, deterministic acquisition, and real-time image processing. By processing image data directly in the FPGA, acquisition, image enhancement, compression, and data preparation can operate within the same deterministic pipeline before data is transferred to downstream processors, storage systems, or networks. This architecture is well suited to applications such as ISR, EO/IR imaging, fixed-camera surveillance, UAV payloads, mission recording, and other high-bandwidth imaging systems. Edge AI with NVIDIA Jetson and FPGA Acquisition Gidel also demonstrated the integration of NVIDIA Jetson computing with FPGA-based image acquisition and processing. The FPGA can handle deterministic camera acquisition and pixel-intensive preprocessing before transferring processed image data to the Jetson. This reduces acquisition and image-processing overhead on the embedded processor and leaves more CPU/GPU resources available for AI inference and application logic. Gidel’s embedded architecture supports high-speed imaging interfaces including CoaXPress, GigE Vision, and Camera Link, enabling compact Edge AI systems for demanding defense and aerospace applications. Real-Time Quality+ Compression and Image Enhancement Gidel demonstrated Quality+ Compression for reducing image data volume directly in the FPGA processing pipeline. Quality+ Compression can reduce bandwidth and storage requirements while maintaining high image quality and low processing latency. Gidel also demonstrated Real-Time HDR IP and other FPGA-based image-enhancement capabilities for imaging systems operating under difficult lighting and visibility conditions. High-Speed Image Acquisition and Recording Gidel’s acquisition platforms support real-time image capture, FPGA processing, recording, and streaming for high-bandwidth imaging systems. Supported machine vision interfaces include: CoaXPress Frame Grabbers for very high-bandwidth acquisition GigE Vision Frame Grabbers for flexible Ethernet-based imaging Camera Link Frame Grabbers for deterministic industrial camera acquisition These interfaces can be combined with FPGA processing, compression, recording, and embedded AI to create compact imaging systems for mission-critical applications. Military & Aviation 2024 Applications ISR and EO/IR imaging systems UAV and airborne imaging payloads Fixed-camera defense and surveillance systems Real-time image enhancement Edge AI detection, tracking, and classification High-bandwidth image acquisition and recording Real-time compression for bandwidth and storage reduction Compact and rugged imaging systems Explore Gidel FPGA Imaging and Edge AI Solutions Gidel PCIe Frame Grabbers FantoVision Edge AI Systems Quality+ Compression Real-Time HDR IP Military & Aviation 2024 Event Details When: Thursday, November 28, 2024 Where: Pavilion 10, Tel Aviv Expo Hosted at: Eastronics Booth - Published: 2024-07-23 - Modified: 2026-09-08 - URL: https://gidel.com/breast-cancer-screening-device-thermomind-case-study/ - Categories: Technical Articles, Case Studies - Tags: Embedded Vision, Medical Imaging, FPGA Processing, Image Acquisition, CoaXPress Frame Grabbers, Edge AI, FPGA Compression, NVIDIA Jetson, Altera FPGA ThermoMind Vision One is an AI breast cancer screening device that combines multimodal thermal, NIR, and 3D imaging with Gidel FantoVision40-CXP12 for high-bandwidth acquisition and real-time FPGA processing. AI Breast Cancer Screening Device with Multimodal Imaging ThermoMind’s Vision One is an AI breast cancer screening device that combines multimodal imaging with advanced AI analysis. The system uses thermal, near-infrared, and 3D sensing to capture physiological and structural information for breast screening research. To acquire and process multiple high-resolution sensor streams in real time, ThermoMind integrated Gidel’s FantoVision edge computing platform into the Vision One system. ThermoMind Vision One and Multimodal Breast Imaging ThermoMind developed Vision One as a supplementary breast imaging technology that combines multiple sensing modalities with AI-based analysis. The system captures more than 300 data points using infrared and depth-sensing technologies to create a digital model of the breast area and analyze thermal, vascular, and structural patterns. The imaging process is contact-free and does not use ionizing radiation. Vision One integrates long-wave infrared, near-infrared, and 3D imaging within a single system. AI-Enhanced Thermal and 3D Imaging The Vision One imaging structure uses multiple infrared and depth sensors positioned around the patient to capture a wide field of view across the breast and axillary areas. AI algorithms analyze the acquired thermal and depth data to identify imaging patterns and digital biomarkers for evaluation within ThermoMind’s clinical studies. The system also includes technician-facing software and supports digital workflows for clinical review and consultation. FantoVision40-CXP12 for High-Bandwidth Medical Imaging ThermoMind partnered with Gidel to address the challenge of acquiring multiple high-resolution sensor streams simultaneously while maintaining real-time processing. Gidel’s FantoVision40-CXP12 combines NVIDIA Jetson computing with an Altera Arria 10 FPGA and integrated CoaXPress-12 acquisition in a compact embedded system. The platform measures approximately 134 × 90 × 60 mm and weighs about 750 g, allowing it to be integrated into space-constrained medical imaging equipment. Vision One uses CoaXPress-connected imaging sensors, making FantoVision40-CXP12 well suited to its high-bandwidth acquisition requirements. 15 Sensors with Real-Time FPGA Acquisition The Vision One architecture uses 15 sensors capturing high-resolution image streams at approximately 30 to 60 frames per second. FantoVision acquires these streams through its FPGA-based imaging pipeline and processes the data before downstream analysis. The FPGA architecture provides deterministic acquisition and allows pixel-intensive operations to run close to the sensors rather than relying entirely on downstream CPU or GPU processing. FantoVision40-CXP12 acquires directly from high-bandwidth CoaXPress cameras, supporting multi-sensor medical imaging systems that require deterministic acquisition and real-time FPGA processing. Real-Time Compression for Multimodal Imaging Data High-resolution multimodal imaging generates large amounts of data, creating significant bandwidth, processing, storage, and transfer requirements. Gidel’s real-time image compression operates directly in the FPGA during acquisition. This allows Vision One to reduce the amount of image data that must move further through the system while maintaining real-time acquisition and processing. ThermoMind identified real-time compression as an important part of the Vision One architecture because it allows image data to be processed during acquisition rather than only afterward. Why FantoVision Fits the Vision One Architecture Vision One required a compact platform capable of combining high-bandwidth image acquisition, FPGA processing, real-time compression, and embedded computing. FantoVision provides these capabilities in a single embedded architecture: High-bandwidth CoaXPress-12 image acquisition Deterministic FPGA processing Real-time image compression NVIDIA Jetson computing for embedded AI and application processing Compact 134 × 90 × 60 mm form factor This integration reduces the need for separate acquisition, processing, and embedded computing hardware inside the medical imaging system. Clinical Evaluation of the ThermoMind Vision One Device ThermoMind is evaluating Vision One through international multicenter clinical studies. The studies evaluate thermal video streams combined with AI algorithms and compare the approach with established breast diagnostic procedures. ThermoMind has reported collaboration with institutions including University Hospital Heidelberg, MD Anderson Cancer Center, and Assuta Medical Centers. The goal is to evaluate the diagnostic performance of the Vision One approach and its potential role as a supplementary breast imaging and screening technology. Gidel FPGA Technology for Medical Imaging Systems The ThermoMind case study demonstrates how Gidel FPGA-based imaging technology can support medical systems that require simultaneous multi-sensor acquisition, deterministic processing, real-time compression, and embedded AI computing. Gidel Medical Imaging Solutions support high-bandwidth imaging architectures including compact embedded systems, FPGA frame grabbers, and custom image-processing platforms. Learn more about FantoVision: FantoVision Edge AI Systems Watch the ThermoMind Vision One case study video: https://www. youtube. com/watch? v=wv3dPIv_4Cg&t=6s - Published: 2024-04-08 - Modified: 2026-09-08 - URL: https://gidel.com/gidel-embedded-vision-platform-embedded-world-2024/ - Categories: Events - Tags: Embedded Vision, Machine Vision, FPGA Processing, Image Acquisition, CoaXPress Frame Grabbers, Edge AI, GigE Vision Frame Grabbers, Camera Link Frame Grabbers, FPGA Compression, Embedded World 2024 At Embedded World 2024 in Nuremberg, Gidel demonstrated FantoVision embedded vision systems with FPGA-based acquisition, NVIDIA Jetson Edge AI, real-time HDR, Quality+ Compression, and high-bandwidth camera interfaces. Embedded World 2024: Gidel Demonstrated Embedded Vision and Edge AI At Embedded World 2024, Gidel demonstrated FPGA-based embedded vision technologies for high-resolution acquisition, real-time image processing, and Edge AI. The demonstrations showed how Gidel combines high-bandwidth camera acquisition, deterministic FPGA processing, and NVIDIA Jetson computing in compact embedded systems for demanding imaging and vision applications. FantoVision Embedded Vision with FPGA Acquisition and NVIDIA Jetson Gidel presented its FantoVision Edge AI Systems, which combine NVIDIA Jetson computing with FPGA-based image acquisition and real-time processing. FantoVision supports high-bandwidth imaging interfaces including GigE Vision, CoaXPress, and Camera Link. The FPGA handles deterministic acquisition and pixel-intensive processing before transferring image data to the Jetson for AI and application processing. This architecture reduces acquisition and image-processing overhead on the embedded processor, leaving more CPU/GPU resources available for inference, detection, tracking, classification, and application logic. High-Bandwidth Camera Acquisition for Embedded Vision Gidel’s embedded vision architecture supports multiple machine vision interfaces for different bandwidth and system requirements: GigE Vision frame grabbers for flexible high-bandwidth Ethernet-based acquisition CoaXPress frame grabbers for very high-bandwidth acquisition, including CXP-12 Camera Link frame grabbers for deterministic industrial camera acquisition Engineers comparing camera interfaces can also review Gidel’s guides to CoaXPress cameras, GigE Vision cameras, and Camera Link cameras. The guides cover bandwidth, connectivity, synchronization, cabling, and acquisition considerations. Real-Time FPGA Processing for Edge AI Gidel demonstrated how FPGA processing can offload image-processing workloads from NVIDIA Jetson processors. The FPGA can perform functions such as image correction, enhancement, HDR, compression, protocol processing, and data preparation directly within the acquisition pipeline. This enables deterministic real-time processing with low added latency while preserving Jetson CPU/GPU resources for AI inference and application workloads. Developers who need custom FPGA processing can use Gidel’s ProcVision Suite to develop and integrate their own FPGA imaging algorithms. Real-Time HDR and Quality+ Compression Gidel also demonstrated FPGA-based image enhancement and data reduction technologies at Embedded World 2024. Real-Time HDR IP improves image visibility in scenes with challenging lighting and high dynamic range while operating directly within the FPGA processing pipeline. Quality+ Compression reduces image data volume in real time while maintaining high image quality, helping reduce downstream bandwidth and storage requirements. Embedded Vision Applications Embedded AI and machine vision Industrial inspection and automation Multi-camera imaging systems High-bandwidth image acquisition Real-time FPGA image enhancement Edge AI detection, tracking, and classification Compact and SWaP-constrained imaging systems Explore Gidel Embedded Vision Platforms FantoVision Edge AI Systems PCIe Frame Grabbers Mini FPGA Modules Embedded World 2024 Event Details When: April 9 to 11, 2024Where: Nuremberg, GermanyBooth: 2-559 Official event website: Embedded World - Published: 2023-09-21 - Modified: 2026-09-08 - URL: https://gidel.com/webinar-overcoming-bandwidth-limitations-when-imaging-on-the-edge/ - Categories: Technical Articles, Webinars & Tech Talks - Tags: Embedded Vision, Machine Vision, FPGA Processing, Image Acquisition, Recording & Streaming, CoaXPress Frame Grabbers, Edge AI, GigE Vision Frame Grabbers, Camera Link Frame Grabbers, FPGA Compression In this Edge Imaging webinar, Gidel CTO Reuven Weintraub explains how FPGA acquisition, FantoVision Edge AI Systems, and real-time compression overcome bandwidth limitations in high-resolution imaging at the edge. Edge Imaging: Overcoming Bandwidth Limitations at the Edge Edge Imaging allows high-resolution camera data to be acquired and processed close to the sensor instead of transferring the full imaging workload to a remote server or cloud system. As camera resolutions and frame rates increase, however, embedded and edge computers can face significant bandwidth, processing, and storage limitations. In this webinar, Gidel Founder and CTO Reuven Weintraub explains how FPGA-based acquisition, processing, and compression can help overcome these limitations while maintaining deterministic real-time operation. Why High-Resolution Edge Imaging Creates Bandwidth Challenges Modern imaging systems generate increasingly large data streams as camera resolution, frame rate, bit depth, and camera count increase. When an embedded CPU or GPU receives these streams directly, acquisition can consume significant system bandwidth and processing resources before the application or AI workload even begins. This challenge becomes especially important in compact embedded systems, where PCIe bandwidth, memory bandwidth, storage capacity, network throughput, power, and thermal limits must all be considered. FPGA Acquisition for High-Bandwidth Vision Gidel uses FPGA-based image acquisition to handle high-bandwidth camera streams before they reach the embedded processor. The FPGA can manage deterministic acquisition, protocol processing, timing, buffering, image preprocessing, and data preparation within the acquisition pipeline. This allows the embedded CPU or GPU to focus more of its resources on AI inference, application processing, control, and other system-level tasks. FantoVision Edge AI Systems for Imaging at the Edge Gidel’s FantoVision Edge AI Systems combine NVIDIA Jetson computing with FPGA-based image acquisition and processing in compact embedded platforms. FantoVision supports high-bandwidth camera interfaces including GigE Vision, CoaXPress, and Camera Link. The FPGA handles acquisition and pixel-intensive processing before transferring image data to the Jetson for AI and application processing. This heterogeneous FPGA and Jetson architecture supports embedded vision applications that require high data rates, low latency, deterministic acquisition, and real-time AI processing. Real-Time Compression Reduces Imaging Data Image compression can reduce the amount of data that downstream processors, storage systems, and networks must handle. Gidel’s FPGA Image Compression IPs operate directly within the FPGA processing pipeline. As a result, the FPGA can compress image data during acquisition before the full uncompressed stream moves deeper into the edge computing architecture. For applications that require high image quality with significant data reduction, Gidel’s Quality+ Compression can further reduce bandwidth and storage requirements while maintaining high image quality. Multiple Camera Interfaces for Embedded Vision Different edge imaging applications require different camera interfaces depending on bandwidth, cabling, distance, synchronization, and system architecture. In addition, Gidel supports embedded and edge imaging systems using GigE Vision, CoaXPress, and Camera Link acquisition. The platform can acquire directly from high-bandwidth CoaXPress cameras, GigE Vision cameras, and Camera Link cameras. This allows FPGA-based acquisition and processing to match different bandwidth, cabling, and system requirements. Applications for High-Bandwidth Imaging at the Edge Embedded AI and machine vision Industrial inspection and automation Multi-camera imaging systems High-resolution image acquisition Real-time recording and streaming Edge AI detection, tracking, and classification Compact and SWaP-constrained vision systems Explore Gidel Edge Imaging Platforms FantoVision Edge AI Systems PCIe Frame Grabbers Mini FPGA Modules Watch the full Edge Imaging webinar above to learn how Gidel combines FPGA acquisition, processing, compression, and embedded computing to overcome high-bandwidth imaging challenges at the edge. For more technical videos, visit the Gidel YouTube Channel. - Published: 2023-06-26 - Modified: 2026-09-09 - URL: https://gidel.com/gidel-camsim-camera-simulator-now-supports-cxp-12-interface/ - Categories: Technical Articles, Press release - Tags: CXP-12, Machine Vision, CoaXPress Frame Grabbers, High-Speed Imaging, CoaXPress Simulators Gidel expands CamSim-X with CXP-12 support, enabling 12.5 Gb/s CoaXPress simulation for high-bandwidth frame grabber development, validation, and system testing. CoaXPress Simulator 12G Support for High-Bandwidth Testing CoaXPress Simulator 12G Support is now available with Gidel CamSim-X, enabling developers to generate higher-bandwidth CXP-12 image streams for testing and validating imaging systems. The update increases the link rate from CXP-6 to 12. 5 Gb/s per link. As a result, engineers can test acquisition systems under more demanding bandwidth conditions. Higher-Bandwidth CoaXPress Testing and Validation Gidel’s CamSim-X CoaXPress Camera Simulator generates controlled video streams and test patterns for frame grabber and imaging-system development. With CXP-12 support, developers can validate higher-bandwidth acquisition pipelines without depending on the final production camera during every development stage. CamSim-X CXP-12 Support Update Area CamSim-X CXP-12 Update Product CamSim-X CoaXPress Camera Simulator Previous Interface Support CXP-6 Added Interface Support CXP-12 Maximum Nominal Link Rate Up to 12. 5 Gb/s per link Main Benefit Higher-bandwidth CoaXPress image-stream simulation and validation Typical Use Frame grabber development, acquisition testing, system integration, debugging, and regression testing Product Platform Same CamSim-X platform with expanded CXP-12 capability Swipe horizontally to view all columns → This allows engineers to reproduce known image sources and test conditions for debugging, validation, and regression testing. CXP-12 Support for Frame Grabber Development The update is particularly useful for developers working with high-speed CoaXPress Frame Grabbers and imaging systems. Typical uses include: CoaXPress frame grabber development and validation CXP-12 acquisition testing High-bandwidth imaging-system integration Repeatable image-stream generation System debugging and regression testing Testing without requiring the final production camera CXP-12 is especially relevant to systems using high-resolution or high-frame-rate cameras, where acquisition bandwidth can quickly become a validation challenge. Controlled simulation lets developers test these higher data rates before the final camera configuration is available. Programmable Video Streams and Test Patterns CamSim-X generates programmable CoaXPress video streams and test patterns that allow developers to control the image source used during system testing. This repeatability helps isolate acquisition problems and verify system behavior under known and reproducible conditions. Software and API Control The simulator includes an intuitive software interface for configuring generated image streams and test patterns. Developers can also control CamSim-X through its API. This enables automated testing, repeatable validation procedures, and integration with system-level test environments. CamSim-X CoaXPress Camera Simulator Adds CXP-12 Support The addition of CXP-12 support expands CamSim-X for developers working with newer high-bandwidth CoaXPress imaging systems. The new CoaXPress Simulator 12G Support helps engineers validate acquisition hardware and software under controlled conditions before the complete camera system is available. By generating controlled 12. 5 Gb/s CoaXPress streams, CamSim-X supports development and validation of high-bandwidth acquisition pipelines for modern CoaXPress systems. Read the inVISION announcement: Camera Simulator with CXP-6 to CXP-12 Learn more: CamSim-X CoaXPress Camera Simulator - Published: 2023-05-31 - Modified: 2026-09-08 - URL: https://gidel.com/fantevision-edge-computer-vision-award-2023/ - Categories: Technical Articles, Press release - Tags: Embedded Vision, Machine Vision, FPGA Processing, Image Acquisition, CoaXPress Frame Grabbers, Edge AI, GigE Vision Frame Grabbers, Camera Link Frame Grabbers, FPGA Compression Gidel FantoVision received a 2023 Vision Systems Design Silver Award for Edge Computer Vision. The platform combines high-bandwidth FPGA acquisition with NVIDIA Jetson computing for compact, low-latency embedded vision systems. Edge Computer Vision: FantoVision Recognized by Vision Systems Design Edge Computer Vision combines high-bandwidth image acquisition, FPGA processing, and embedded AI computing close to the camera or sensor. On May 22, 2023, Gidel’s FantoVision platform received a Silver Award in the Vision Systems Design Innovators Awards program during Automate 2023 in Detroit. The recognition highlighted FantoVision’s integration of FPGA-based image acquisition with NVIDIA Jetson computing. This architecture supports compact, high-performance embedded vision systems. Why FantoVision Stands Out for Edge Computer Vision FantoVision combines Gidel’s FPGA-based acquisition and image-processing technology with NVIDIA Jetson computing in a compact embedded platform. The FPGA handles deterministic camera acquisition and pixel-intensive processing before image data is transferred to the Jetson for AI inference and application processing. This architecture reduces acquisition and preprocessing overhead on the embedded processor. As a result, more CPU/GPU resources remain available for detection, tracking, classification, and application logic. High-Bandwidth Camera Acquisition at the Edge FantoVision supports high-bandwidth imaging interfaces including GigE Vision, CoaXPress, and Camera Link. The platform can acquire directly from high-bandwidth CoaXPress cameras, GigE Vision cameras, and Camera Link cameras. This allows FPGA-based acquisition and processing to match different bandwidth, cabling, and system requirements. FPGA Processing for Embedded AI Vision FantoVision uses FPGA processing for protocol handling, image enhancement, compression, HDR, buffering, timing, and data preparation. These functions run directly within the acquisition pipeline. By moving these pixel-intensive operations into the FPGA, the system maintains deterministic real-time behavior. At the same time, it preserves Jetson resources for embedded AI workloads. FantoVision Edge AI Systems Gidel’s FantoVision Edge AI Systems support compact embedded vision architectures. They combine high data rates, low latency, FPGA processing, and NVIDIA Jetson AI computing. Typical applications include industrial inspection, robotics, autonomous systems, and multi-camera imaging. These workloads require high-bandwidth acquisition and real-time processing to operate together. 2023 Vision Systems Design Innovators Award Vision Systems Design announced the 2023 Innovators Awards honorees at Automate 2023 in Detroit. The program recognizes machine vision and imaging products for originality, innovation, market impact, and practical value. It considers the needs of designers, system integrators, and end users. Gidel received a Silver Award for FantoVision. The award recognized its combination of FPGA-based image acquisition and NVIDIA Jetson processing in an embedded edge vision system. Learn more about FantoVision: FantoVision Edge AI Systems Official Vision Systems Design award announcement: 2023 Innovators Awards Honorees - Published: 2023-02-10 - Modified: 2026-09-09 - URL: https://gidel.com/high-speed-image-acquisition/ - Categories: Technical Articles - Tags: Embedded Vision, High-Resolution Imaging, Machine Vision, FPGA Processing, Image Acquisition, Recording & Streaming, CoaXPress Frame Grabbers, Edge AI, GigE Vision Frame Grabbers, Camera Link Frame Grabbers, FPGA Compression, High-Speed Imaging High-speed image acquisition can generate several gigapixels per second, creating major bandwidth and processing challenges. Learn how FPGA acquisition, preprocessing, compression, and Edge AI architectures maintain real-time vision performance. High-Speed Image Acquisition in Modern Vision Systems High-Speed Image Acquisition has become a central requirement in modern machine vision and imaging systems. High-resolution and high-frame-rate cameras can generate several gigapixels per second, creating significant demands on acquisition bandwidth, memory, processing, storage, and downstream computing. A system processing several gigapixels per second must continuously acquire, move, and often preprocess billions of pixels every second without dropping frames. Maintaining real-time performance requires more than a fast camera interface. The complete acquisition path must sustain the incoming data rate while preserving deterministic timing, low latency, and reliable image transfer. Why Gigapixel Data Rates Create Acquisition Bottlenecks As camera resolution, frame rate, bit depth, and camera count increase, imaging systems must continuously move and process much larger data streams. High-bandwidth interfaces such as CoaXPress, GigE Vision, and Camera Link can deliver large volumes of image data into the system. However, acquisition is only the first stage. The architecture must also handle buffering, preprocessing, image enhancement, compression, memory transfers, and application processing without losing frames. This is especially challenging when the system must process multiple gigapixels per second while maintaining predictable latency. FPGA Architecture for High-Speed Image Acquisition FPGA-based acquisition allows image data to move directly from the camera interface into dedicated processing logic. The FPGA can handle deterministic acquisition, protocol processing, buffering, timing, image preprocessing, and data preparation before transferring image data to the host CPU, GPU, or embedded processor. This architecture helps reduce the amount of acquisition and pixel-processing work performed by general-purpose processors. As a result, CPU and GPU resources remain available for AI inference, application logic, visualization, and other higher-level workloads. Real-Time FPGA Preprocessing Before the CPU or GPU High-speed acquisition becomes more efficient when pixel-intensive processing occurs close to the camera input. The FPGA can perform operations such as image correction, HDR, compression, filtering, buffering, and data preparation directly within the acquisition pipeline. Processing data before it reaches the CPU or GPU can reduce downstream memory traffic and processing requirements while maintaining deterministic real-time operation. Reducing Gigapixel Data with FPGA Compression High-speed imaging systems can also generate significant storage and network demands. Real-time compression helps reduce the amount of image data that must move through the rest of the system. Gidel’s FPGA Image Compression IPs operate directly within the FPGA processing pipeline. For applications requiring high image quality with substantial data reduction, Quality+ Compression can reduce bandwidth and storage requirements while maintaining high image quality. High-Speed Image Acquisition with Edge AI Gidel’s FantoVision Edge AI Systems combine high-bandwidth FPGA acquisition and processing with NVIDIA Jetson computing. The FPGA handles deterministic camera acquisition and pixel-intensive processing before transferring image data to the Jetson. This leaves more CPU/GPU resources available for AI inference, detection, tracking, classification, and application processing. High-Bandwidth Camera Interfaces High-Speed Image Acquisition Interface Comparison Area CoaXPress GigE Vision Camera Link Architecture Dedicated point-to-point camera interface Ethernet-based network architecture Dedicated parallel camera interface Nominal Interface / Link Rate Very high, including 12. 5 Gb/s per CXP-12 link Scalable across multiple Ethernet speeds, including 1, 2. 5, 5, and 10 GigE Vision Up to approximately 6. 8 Gb/s with 80-bit Deca configurations Cabling Coaxial cable Copper or fiber Ethernet Dedicated Camera Link cabling Camera Power PoCXP available PoE available on compatible systems PoCL available on compatible systems Multi-Camera Scaling Multiple dedicated links or frame grabbers Flexible switched Ethernet networking Multiple frame-grabber channels Typical Strength Very high bandwidth and deterministic point-to-point acquisition Long reach, networking flexibility, and scalable camera connectivity Established deterministic industrial acquisition Typical Applications High-resolution, high-frame-rate, scientific, defense, and advanced inspection Distributed imaging, machine vision, robotics, inspection, and multi-camera systems Industrial inspection, sorting, scientific imaging, and established machine vision systems Swipe horizontally to view all columns → Different high-speed image acquisition systems require different camera interfaces depending on bandwidth, distance, cabling, synchronization, and system architecture. Gidel supports high-bandwidth acquisition through: CoaXPress Frame Grabbers for very high-bandwidth acquisition, including CXP-12 GigE Vision Frame Grabbers for flexible Ethernet-based high-speed imaging Camera Link Frame Grabbers for deterministic industrial camera acquisition Gidel’s acquisition platforms can acquire directly from high-bandwidth CoaXPress cameras, GigE Vision cameras, and Camera Link cameras. This allows FPGA-based acquisition and processing to match different bandwidth, cabling, and system requirements. Applications for High-Speed Image Acquisition High-resolution industrial inspection Multi-camera machine vision Semiconductor and scientific imaging Real-time recording and streaming Embedded AI and Edge AI vision High-speed image processing Gigapixel imaging systems Explore Gidel High-Speed Image Acquisition Platforms PCIe Frame Grabbers FantoVision Edge AI Systems Mini FPGA Modules - Published: 2023-01-29 - Modified: 2026-09-09 - URL: https://gidel.com/embedded-vision-system-fantovision20-40/ - Categories: Technical Articles, Press release - Tags: Embedded Vision, Machine Vision, FPGA Processing, Image Acquisition, CoaXPress Frame Grabbers, Edge AI, GigE Vision Frame Grabbers, Camera Link Frame Grabbers, FPGA Compression, High-Speed Imaging, NVIDIA Jetson Gidel integrates the NVIDIA Jetson Orin NX 16GB into the FantoVision series, creating a breakthrough heterogeneous embedded vision system. With 157 TOPS of AI performance and FPGA-based acceleration, this platform sustains over 1 gigapixel per second, redefining real-time high-bandwidth imaging at the edge. Redefining Edge Imaging with Breakthrough Heterogeneous Computing Big news for vision, imaging, and AI applications. Gidel introduces the first heterogeneous computer that combines NVIDIA Jetson Orin NX with an FPGA-based acquisition and acceleration engine, creating an exceptionally powerful embedded vision system for real-time, high-bandwidth imaging at the edge. The new configuration brings the NVIDIA Jetson Orin NX 16GB module into the FantoVision20 and FantoVision40 product line. With current NVIDIA JetPack support, the Jetson Orin NX 16GB can deliver up to 157 sparse TOPS in MAXN_SUPER mode, providing up to approximately five times the AI compute performance of the previous Jetson Xavier NX generation. As a result, developers gain substantially higher AI throughput, deterministic FPGA acquisition, and real-time image processing capabilities. When paired with Gidel’s FPGA-based frame grabbing, pre-processing, and compression, the platform sustains more than 1 gigapixel per second of imaging throughput. FantoVision: A Complete Embedded Vision System for High-Speed Imaging The FantoVision series provides a ready-to-use environment for advanced imaging and AI applications. Each system integrates: NVIDIA Jetson Orin NX 16GB Gidel’s FPGA image acquisition and acceleration engine High-bandwidth camera connectivity Real-time compression and enhancement options Compact, industrial-grade mechanics SWaP-optimized design: 134 × 90 × 60 mm, 750 g Therefore, developers can deploy real-time and high-resolution vision systems with shorter integration cycles and improved reliability. Multi-Interface Flexibility for Demanding Vision Applications The FantoVision20 integrates Camera Link and GigE Vision within the same compact edge computer. Consequently, system designers gain flexibility when selecting the right camera interface for their industrial vision pipeline. The FantoVision40 model supports high-bandwidth CoaXPress-12 imaging and can also be configured with optional 10GigE Vision connectivity. This gives developers additional flexibility for high-speed and multi-camera system architectures while maintaining deterministic performance. Together, the FantoVision20 and FantoVision40 platforms deliver versatile, multi-interface embedded vision systems. As a result, designers can address a wide range of machine vision requirements with a common heterogeneous architecture. FantoVision20 vs FantoVision40 Embedded Vision Systems Feature FantoVision20 FantoVision40 Primary Camera Interfaces GigE Vision and Camera Link CoaXPress-12 Maximum Interface Bandwidth Up to 20 Gb/s GigE Vision, 6. 8 Gb/s Camera Link, or up to 26. 8 Gb/s in combined GigE Vision + Camera Link configurations Up to 4 × CXP-12 links, 50 Gb/s aggregate interface bandwidth 10 GigE Vision Supported Optional configuration FPGA Processing Deterministic acquisition, preprocessing, compression, and custom FPGA processing Deterministic acquisition, preprocessing, compression, and custom FPGA processing Embedded AI NVIDIA Jetson computing for AI and application processing NVIDIA Jetson computing for AI and application processing Typical System Fit GigE Vision, Camera Link, dual-interface, and flexible multi-camera systems Very high-bandwidth CoaXPress and multi-sensor imaging systems Swipe horizontally to view all columns → FantoVision can acquire directly from high-bandwidth CoaXPress cameras, GigE Vision cameras, and Camera Link cameras, allowing system designers to match the acquisition interface to bandwidth, cabling, synchronization, and application requirements. Jetson Orin NX + FPGA Acceleration Enables Real-Time AI Vision The NVIDIA Jetson Orin NX combines CPU and GPU computing for AI workloads, while the integrated Gidel FPGA handles deterministic image acquisition, preprocessing, and acceleration. In addition, the integrated FPGA performs: High-speed frame grabbing and ROI extraction Real-time image enhancements such as HDR Compression (JPEG, lossless, H. 264/H. 265, Quality+) This heterogeneous architecture enables FantoVision to sustain more than 1 gigapixel per second of imaging throughput. Meanwhile, NVIDIA JetPack supports the Jetson software and AI environment. A Turnkey Platform for Embedded AI Vision Systems “The combination of Gidel’s FPGA and image-processing expertise with NVIDIA accelerated computing breaks another barrier between AI and machine vision,” said Reuven Weintraub, Founder and CTO of Gidel. This heterogeneous architecture, which brings FPGA and GPU processing together in one embedded vision system, gives engineers a turnkey platform for running AI workloads alongside real-time, high-speed imaging. Gidel showcased the Jetson Orin NX-enabled FantoVision systems at Embedded World 2023 in Nuremberg, Germany, held March 14–16, 2023. - Published: 2022-12-27 - Modified: 2026-09-09 - URL: https://gidel.com/enabling-high-speed-aoi-machines-for-sorting-applications/ - Categories: Technical Articles, Case Studies - Tags: Embedded Vision, Machine Vision, AOI, FPGA Processing, Image Acquisition, Camera Link Frame Grabbers, FPGA Compression, High-Speed Imaging Discover how a leading mail sorting manufacturer leveraged Gidel’s FPGA-based vision infrastructure to optimize high-speed AOI Machines. By integrating the HawkEye-CL frame grabber, this solution achieves the deterministic latency and multi-camera synchronization required for accurate, continuous automated inspection. High-Speed AOI Machines for Mail Sorting AOI machines are a fundamental element in modern mail sorting environments, where envelopes and parcels move continuously and inspection must keep pace with the mechanical speed of the line. In high-speed AOI machines, visual verification, identification, and routing decisions must happen within a fixed timing window. Otherwise, even small delays or variability can directly affect sorting accuracy and operational efficiency. For this reason, a leading mail sorting equipment manufacturer integrated Gidel’s FPGA-based vision infrastructure into its AOI machines. This integration enables a hardware-driven inspection pipeline that combines high-speed operation with reliable and accurate inspection results in production. As a result, the system operates on a continuous sorting line, where items pass through the inspection zone without stopping or buffering. At the same time, multiple cameras capture image data simultaneously, covering different regions of each envelope. The system then delivers inspection results in time to trigger downstream sorting actions. This operational model places strict demands on synchronization, latency consistency, and sustained throughput. The Challenge of High-Speed AOI Machines Designing AOI machines for high-speed mail sorting presents several interconnected challenges that grow as throughput and camera count increase. The inspection system must process images from multiple cameras in parallel and operate continuously without performance degradation. At the same time, it must deliver results that align precisely with mechanical actuators and routing logic. If the system relies too heavily on host CPU load or operating system scheduling, timing jitter can appear. Consequently, inspection reliability and sorting accuracy can degrade over time. To avoid this risk, the vision architecture must prioritize predictable behavior under sustained load. High-speed continuous motion: The system must inspect items on the fly without slowing the sorting line. Multi-camera inspection: Multiple cameras must cover different inspection regions in a single pass. Deterministic timing: The system must deliver inspection and routing decisions within a fixed latency budget. Continuous operation: AOI machines must run reliably for long periods under sustained throughput. FPGA Vision Infrastructure Inside High-Speed AOI Machines To address these challenges, the AOI machines rely on a hardware-centric vision architecture. In this design, FPGA-based frame grabbers handle image acquisition and preprocessing directly. This approach reduces dependence on host CPU resources and operating system scheduling. As a result, the system maintains consistent acquisition timing and stable data delivery even during peak throughput. At the same time, the architecture preserves inspection accuracy under continuous operation. The customer used the HawkEye-CL Camera Link frame grabber as the core acquisition platform for multiple Camera Link cameras installed in the AOI machines. By anchoring acquisition on the FPGA, the system delivers deterministic frame timing, reliable camera synchronization, and stable data transfer into the processing pipeline, providing clean, consistent images that maximize the accuracy of downstream OCR and barcode reading algorithms. The HawkEye-CL acquires directly from Camera Link cameras, supporting deterministic multi-camera acquisition for high-speed AOI systems. In addition, this implementation reflects Gidel’s broader portfolio of PCIe FPGA Frame Grabbers, which target high-bandwidth, low-latency, multi-camera AOI applications where predictable behavior and inspection quality are equally important. What the Frame Grabber Enables in AOI Machines At the system level, the frame grabber serves as both a data capture device and a timing anchor for the inspection process. By performing acquisition and preprocessing close to the cameras, the AOI machines maintain consistent behavior regardless of downstream processing load. Deterministic multi-camera image acquisition FPGA-based preprocessing close to the sensor Stable latency under sustained inspection load Reliable synchronization across inspection zones Managing AOI Image Data with FPGA-Based Compression High-speed AOI machines generate large volumes of image data, especially during continuous multi-camera operation. Without data reduction, bandwidth and storage can quickly become system bottlenecks. To prevent this, the OEM leveraged FPGA Image Compression IPs directly on the frame grabber. This approach reduces downstream data rates while preserving image quality required for inspection, verification, and classification tasks. As a result, the system maintains predictable behavior even at high line speeds. Embedded AOI Processing with Jetson and FPGA In AOI machine designs that require compact, embedded processing close to the inspection point, the architecture aligns naturally with Gidel’s FantoVision Edge AI Systems. These platforms combine FPGA-based image acquisition with NVIDIA Jetson processing. Consequently, OEMs can integrate inspection logic, AI inference, recording, and control applications in a single platform. At the same time, the system preserves a deterministic hardware foundation that supports both speed and accuracy. Operational Impact on High-Speed AOI Machines By integrating FPGA-based vision infrastructure into the AOI machines, the OEM achieved stable throughput during continuous high-speed operation. The system also delivers predictable inspection latency that supports accurate routing decisions. In addition, FPGA offload reduces sensitivity to CPU load and operating system variability. Together, these improvements translate into higher system reliability and smoother long-term operation on the sorting line. Stable throughput under continuous operation Consistent inspection latency for accurate sorting Reduced CPU load through FPGA offload Improved operational stability and inspection reliability FPGA-Based Vision for High-Speed AOI Machines This case study demonstrates how Gidel’s technology enables high-speed AOI machines while maintaining reliable, real-time, and accurate inspection. By anchoring the vision pipeline on deterministic FPGA-based acquisition and preprocessing, and by integrating frame grabbers, compression technologies, and embedded vision platforms, the system achieves the combination of speed, accuracy, and long-term stability required in demanding mail sorting environments. Revolutionizing Mail Sorting - Published: 2022-10-19 - Modified: 2026-08-27 - URL: https://gidel.com/compressing-image-data-not-image-quality/ - Categories: Technical Articles - Tags: compression, Lossless Compression, FantoVision, Frame Grabbers, Low-Latency, Frame Grabber, Acquisition, High-Bandwidth, High-Resolution Sensors, Quality+ Compression, Image Compression, infiniVision, Acceleration, FPGA Processing, Data Optimization, Data Reduction As modern sensors drive data rates to gigapixel levels, standard codecs often sacrifice detail for bandwidth. This article explores how Gidel Quality+ technology solves this trade-off by delivering high quality image compression directly on the FPGA, enabling real-time processing without compromising image quality. High quality image compression is becoming essential as today’s cameras deliver higher resolutions and higher frame rates, while edge-based systems often operate under strict bandwidth limits. As a result, compression has become a key requirement for advanced image processing. The challenge is clear: how can developers reduce data throughput without jeopardizing inspection accuracy or overall image quality? Growth of High-Resolution Sensors A major trend in the machine vision industry has been the rise of new-generation CMOS sensors that deliver high-resolution images at high frame rates. In earlier inspection systems, cameras below one megapixel were standard, and even five megapixels was once considered a high resolution for industrial applications. Today, 12-, 16-, 20-, or 25-megapixel sensors—such as Sony’s IMX54x family—are common across the industry. You can also find cameras with resolutions above 100 megapixels for advanced vision tasks. Rising Bandwidth Requirements Higher resolutions and faster frame rates naturally require higher interface bandwidth. This is why interfaces such as USB3 Vision, 5GigE, 10GigE, CoaXPress, and Camera Link have expanded rapidly in recent years. These standards deliver the bandwidth required for demanding machine vision applications. Impact on Host Systems As image sizes grow, host computers and processing software must handle enormous data volumes. Traditionally, machine vision systems were stand-alone stations using powerful PCs to process everything locally. Today, vision is increasingly deployed in mobile and outdoor applications that rely on embedded computers and network connectivity for cloud or edge computing. Even when sensors and interfaces manage the raw image flow efficiently, the host still faces significant bandwidth pressure. This makes efficient compression essential. Trade-Offs of Compression Lossless compression algorithms preserve the original image but typically achieve only about a 2:1 compression ratio. This is often insufficient for high-resolution or high-frame-rate applications. Developers face a difficult trade-off: prioritize compression ratio or maintain image quality. Algorithms such as MPEG can reduce image volume by factors of ten and beyond. However, they introduce visible degradation, especially around object edges. While this may be acceptable in consumer video or simple archival use, precision imaging tasks can suffer from even small quality losses. Edge artifacts, noise amplification, and fine-detail loss may all degrade final inspection or analysis results. Generic video codecs are also designed for YUV 4:2:2 or 4:2:0 or RGB movies. They reduce color resolution by design. They also assume that high-frequency noise is acceptable—or even desirable—to enhance perceived sharpness. Many of today’s industrial applications require clean edges, reliable zooming, and stable fine-detail reconstruction. In such cases, high-frequency noise becomes a serious limitation. Gidel’s Approach to High-Quality Compression Gidel, an Israeli company specializing in FPGA development for vision applications, has addressed this challenge for more than 25 years. The company patented Gidel Imaging, a software tool that enhanced compressed images by estimating DCT values before quantization to reduce high-frequency noise during zooming. With its current Quality+ technology, Gidel eliminates or significantly reduces this noise at the source, supporting high quality image compression in demanding applications. Today, Gidel introduces Gidel Quality+ Compression, developed to meet the needs of modern imaging systems. Quality+ provides high compression ratios while maintaining the image quality required for inspection. It can process more than one gigapixel per second per camera in real time on an FPGA with low power consumption, making it ideal for embedded computing. Image Compression at the Acquisition Stage Quality+ Compression supports multi-camera vision systems at full line speed. It runs on FPGAs integrated into Gidel’s high-performance frame grabbers and FantoVision embedded computers. System engineers can also build custom acquisition devices using Gidel’s FPGA modules. Performing compression at the earliest acquisition stage reduces the load on CPU and GPU resources. It prevents bottlenecks between the frame grabber and the host processor and reduces the amount of data that must be processed, stored, or uploaded in edge-based systems. Quality+ uses minimal FPGA resources, enabling Gidel’s InfiniVision platform to grab and compress ten or more cameras running at one gigapixel per second each in real time. This supports high-speed and high-resolution imaging in systems with strict SWaP constraints. Balancing Compression Ratio and Image Quality To meet today’s high-resolution and high-speed imaging requirements, compression algorithms must deliver high ratios while preserving the quality required for inspection. Each application defines image quality differently, so the optimal balance requires a flexible and customizable approach. (This article was published in German in Inspect magazine. ) - Published: 2022-03-28 - Modified: 2026-06-17 - URL: https://gidel.com/fpga-wireless-research/ - Categories: Case Studies, Press release - Tags: Low-Latency, FPGA Accelerator, TU Berlin, research, Wireless Discover how TU Berlin utilizes Gidel technology in their latest FPGA wireless research to enable real-time Massive MIMO processing. This project demonstrates how Gidel’s FPGA Accelerator Cards accelerate 5G and 6G innovation by delivering the deterministic performance and extremely low latency required for next-generation communication systems. This FPGA wireless research project from TU Berlin shows how Gidel’s FPGA technology enables real-time Massive MIMO processing for advanced wireless communication. As a result, researchers can accelerate 5G and 6G innovation with deterministic performance and extremely low latency. This FPGA wireless research highlights the importance of real-time processing in next-generation communication systems. As a result, researchers can accelerate 5G and 6G innovation with deterministic performance and extremely low latency. Learn more about Gidel FPGA Accelerator Cards. About the TU Berlin EECS Department: TU Berlin EECS. Advancing FPGA-Based Wireless Research for Massive MIMO As 5G continues to expand, researchers are exploring ways to deliver higher bandwidth efficiency. With the rapid growth of IoT devices and autonomous systems, networks must exchange data with many terminals in real time. Consequently, the demand for new wireless architectures is increasing. Massive MIMO is one of the leading technologies addressing this need. It uses large antenna arrays that communicate with multiple users simultaneously. SDMA (Space Division Multiple Access) analyzes the unique characteristics of each terminal, optimizing the downlink and ensuring efficient use of available radio resources. Real-Time Challenges in Next-Generation Wireless Systems The main obstacle in Massive MIMO is the requirement for extremely fast, deterministic processing. Because every antenna interacts with every terminal, complex encoding and decoding must happen immediately. However, mobile users constantly move, which means the system must update calculations continuously. FPGAs are ideal for this task due to their predictable timing, parallelism, and very low latency. How TU Berlin Advances FPGA Wireless Research with Gidel Technology The research team led by Prof. Giuseppe Caire at TU Berlin investigates new models for 5G and 6G communication. Their experimental system validates advanced beamforming and real-time wireless processing concepts. Furthermore, the team selected Gidel FPGA hardware—recommended by Intel—to ensure high throughput and precise timing. Real-Time Processing for Wireless FPGA Research The prototype demonstrates that a single Gidel FPGA board can communicate with eight terminals at once, often with fewer radio resources than a traditional base station needs for one user. All antenna streams pass through a single FPGA platform, which connects to RF front-ends and network infrastructure using multi-gigabit transceivers and PCIe. Additionally, Intel Arria 10 FPGAs were chosen for their floating-point performance and exceptional data bandwidth. Scaling Wireless Infrastructure Efficiently Massive MIMO systems depend on beamforming to reduce interference and improve link quality. Adding antennas improves accuracy. For example, TU Berlin’s prototype—designed by Dr. -Ing. Andreas Benzin—uses 64 antennas driven by a single Gidel FPGA board. In commercial designs, one Gidel board could support up to 192 antennas. Moreover, multiple boards can be added to scale the platform further. This work is an important milestone in ongoing FPGA wireless research focused on scaling antenna arrays and improving spectral efficiency. Long-Term Engineering Partnership Gidel has supported the TU Berlin research team for more than 15 years. “It all started in 2005,” notes Dr. -Ing. Andreas Kortke. “We were able to focus on our algorithms from day one instead of wasting time building drivers or host interfaces. ” In addition, upgrading to newer Gidel platforms remained simple thanks to consistent hardware architecture and a stable API across generations. Enabling the Future of Wireless Connectivity As IoT, autonomous vehicles, and edge computing continue to evolve, the demand for fast and reliable wireless systems will grow. Gidel’s FPGA technology helps meet these requirements by providing high throughput, deterministic real-time processing, and a scalable platform for advanced communication research. As Gidel CEO Reuven Weintraub explains: “This application demonstrates the potential of our FPGA technology whenever high throughput and real-time processing are required. ” Download chart (JPG) - Published: 2021-07-21 - Modified: 2026-09-09 - URL: https://gidel.com/embedded-computer-vision-fantovision-20/ - Categories: Technical Articles, Press release - Tags: Embedded Vision, Machine Vision, FPGA Processing, Image Acquisition, Recording & Streaming, Edge AI, GigE Vision Frame Grabbers, Camera Link Frame Grabbers, FPGA Compression, NVIDIA Jetson, Altera FPGA Discover FantoVision20, an ultra-compact embedded computer vision system combining NVIDIA Jetson computing with Altera Arria 10 FPGA acquisition and processing. It supports real-time imaging, compression, and high-bandwidth camera acquisition up to 20 Gb/s. FantoVision20 Embedded Computer Vision System The ultra-compact FantoVision20 embedded vision computer delivers real-time image acquisition, compression, and processing at up to 20 Gb/s. Designed for embedded computer vision workloads, it enables high-speed, high-resolution imaging in systems with strict SWaP limits. As a result, it serves demanding industrial, mobile, and outdoor applications. For more details regarding the FantoVision20 edge AI system, visit: FantoVision20 Ultra-compact embedded computer vision system for 20 Gb/s imaging Gidel, a technology leader in high-performance FPGA systems, introduces a small and robust platform tailored for embedded computer vision and high-throughput processing. FantoVision 20 allows image processing, compression, and recording of video streams up to 20 Gb/s in real time. It delivers this performance in an extremely compact form factor, enabling integration where size and power budgets are limited. High-Speed Image Acquisition and Real-Time Processing With 2 × 10GigE and Camera Link 80-bit (DECA) inputs, FantoVision20 provides high-bandwidth camera interfaces. This allows the system to capture and process high-resolution images at fast frame rates in real time. FantoVision20 can acquire directly from high-bandwidth GigE Vision cameras and Camera Link cameras, supporting flexible embedded vision architectures for high-speed and multi-camera imaging. The architecture combines NVIDIA Jetson computing for AI and application processing with an Altera Arria 10 FPGA for deterministic image acquisition, preprocessing, and compression. Developers can use C/C++, CUDA, and the NVIDIA JetPack software environment for AI and application development. Meanwhile, the FPGA enables advanced preprocessing and FPGA Image Compression IPs for real-time data reduction. With multiple FantoVision20 units and Gidel’s open-FPGA InfiniVision flow, integrators can capture and synchronize more than 1,000 camera streams in scalable systems. Thanks to its 134 × 90 × 60 mm³ form factor, FantoVision20 fits easily into tight installations. Its rugged housing withstands harsh industrial environments, and both passive and active cooling configurations are available. Embedded Computer Vision Applications With its strong processing capabilities and compact design, FantoVision 20 enables new embedded computer vision deployments. Typical applications include high-speed inspection, ITS, broadcast, medical imaging, agriculture, and aerial mapping. High-bandwidth interfaces and real-time processing also enable sorting and inspection tasks at high resolution. A 10GigE switch can connect multiple GigE cameras for 360° inspection or 3D scanning. NVIDIA AI tools support machine learning and inference pipelines. Due to its compression support and size, it can also serve as a portable offline recording system. For surveillance or traffic monitoring, FantoVision 20 enables compression, local recording, and streaming. Its compact housing installs easily on poles or gantries, and long cable interfaces allow flexible placement relative to cameras. The lightweight, low-power design also supports vehicle-based systems, such as 360° mapping, agricultural vision tools, weed detection, targeted fertilization, and autonomous harvesting. With high-bandwidth camera interfaces, NVIDIA Jetson AI processing, and FPGA-based acquisition and preprocessing, FantoVision20 supports demanding embedded computer vision applications while remaining compact and SWaP-efficient. Download press release (PDF) - Published: 2021-02-22 - Modified: 2026-09-09 - URL: https://gidel.com/stratix-10-nx-fpga-module/ - Categories: Technical Articles, Press release - Tags: Machine Vision, FPGA Processing, Image Acquisition, Altera Stratix 10 NX, High-Performance Computing (HPC) Gidel’s Proc10N FPGA Module and Proc1C10N PCIe Board bring Stratix 10 NX AI Tensor Blocks, 400 GB/s HBM2 throughput, and high-bandwidth I/O to compact FPGA platforms for AI, vector processing, radar, 5G, and other compute-intensive applications. Stratix 10 NX FPGA Module for AI and Vector Processing The Stratix 10 NX module marks a major step forward in AI acceleration and vector processing for embedded and high-bandwidth systems. Gidel brings this architecture to ready-to-use module and PCIe board platforms. Developers can therefore implement high-throughput AI and vector-processing workloads in compact FPGA systems. Proc10N and Proc1C10N: Stratix 10 NX Platforms Gidel has released its Proc10N FPGA Module and Proc1C10N PCIe Board, the first commercial platforms built around the Altera Stratix 10 NX. These compact, high-performance solutions target compute-intensive applications that require high data rates and low latency. Stratix 10 NX integrates AI Tensor Blocks for deep-learning acceleration. It also combines them with high-bandwidth HBM2 memory to provide high compute density and memory throughput. Proc10N vs Proc1C10N Stratix 10 NX Platforms Area Proc10N Proc1C10N Platform Type Compact FPGA module PCIe FPGA accelerator board FPGA Architecture Altera Stratix 10 NX Altera Stratix 10 NX AI Acceleration Stratix 10 NX AI Tensor Blocks Stratix 10 NX AI Tensor Blocks High-Bandwidth Memory Integrated HBM2 architecture Integrated HBM2 architecture System Integration Integrates with a Gidel carrier board or customer-designed carrier Installs directly into a PCIe host system Custom Hardware Integration Well suited to compact embedded and custom carrier-board designs Well suited to PCIe host-based acceleration systems Evaluation and Development Supports evaluation, FPGA development, and transition to custom module-based systems Provides a ready-to-use PCIe platform for evaluation and application development Typical System Fit Compact embedded, customized FPGA, and high-bandwidth module-based systems PCIe acceleration, AI, vector processing, and high-bandwidth host systems Swipe horizontally to view all columns → Gidel, a Titanium member of the Intel Partner Alliance, was among the first companies to bring this FPGA architecture to a commercially available module and PCIe platform. AI, Vector Processing, Security, and High-Bandwidth Applications The combination of AI Tensor Blocks and HBM2 memory enables Stratix 10 NX to address real-time, high-throughput workloads. Proc10N and Proc1C10N can support applications such as AI inference, video analytics, cybersecurity, 5G processing, radar, and other bandwidth-intensive algorithms. The compact platform architecture also supports embedded, low-power, and weight-constrained systems where high compute density and high-bandwidth data movement are important design requirements. High-Bandwidth Performance of the Proc10N Module The Proc10N module supports 1,600 Gb/s of customizable I/O, up to 143 INT8 TOPS through the Stratix 10 NX AI Tensor Block architecture, and 400 GB/s of HBM2 throughput. This processing capability supports convolution layers, FFTs, encoders, linear algebra, filtering, and other highly parallel workloads. Despite its performance, the module remains compact at only 97. 4 × 101 mm. This supports integration into space-constrained systems. Intel reported up to a 9. 5× acceleration factor for LSTM batch processing compared with an NVIDIA V100 GPU in its Stratix 10 NX benchmark testing. FPGA Development with ProcVision and Proc Dev Kit Gidel’s modular development tools help developers build FPGA-based systems while reducing integration effort, project risk, and development complexity. The Proc10N module can be integrated with Gidel carrier boards or with a user-designed carrier through the Proc Dev Kit. The ProcVision Suite supports FPGA development and system integration through a unified environment for acquisition, buffering, FPGA flows, debugging, simulation, and host communication. Developers can therefore focus more effort on application algorithms rather than low-level infrastructure. The Proc Dev Kit supports hardware configuration and real-time system testing. It generates Application Support Packages (ASP) matched to each system configuration. These packages help accelerate FPGA-to-host integration and application development. ProcVision also supports distributed multi-unit acquisition, enabling synchronized capture across multiple cameras or sensors. This capability can support robotics, autonomous systems, 360° imaging, high-volume inspection, and other distributed acquisition architectures. The Mini FPGA Modules portfolio also includes Proc10N, supporting compact, high-performance FPGA system integration. Proc10N Availability and Custom FPGA Designs Proc10N and Proc1C10N can also serve as evaluation and development platforms for engineers assessing Stratix 10 NX technology before moving to custom FPGA system designs. Gidel and its partners support developers evaluating Stratix 10 NX platforms. They also assist with new FPGA-based systems that require high-bandwidth I/O, HBM2 memory, AI acceleration, or vector processing. Developers can contact Gidel for assistance with platform selection, carrier-board integration, FPGA development, and custom system design. Download Press Release (PDF) - Published: 2020-02-11 - Modified: 2026-09-09 - URL: https://gidel.com/fpga-vs-gpu-interview/ - Categories: Technical Articles, Webinars & Tech Talks - Tags: Embedded Vision, Machine Vision, FPGA Processing, Image Acquisition, Edge AI, FPGA Compression, NVIDIA Jetson Explore the FPGA vs GPU debate through insights from Gidel’s CTO. Learn where FPGA architectures can offer advantages in deterministic latency, high-bandwidth dataflow, real-time processing, and how FPGA + GPU systems combine complementary strengths for demanding AI and imaging workloads. FPGA vs GPU in High-Performance Computing This FPGA vs GPU interview examines how the two architectures differ in high-performance computing. Comparing a Field Programmable Gate Array (FPGA) vs a Graphics Processing Unit (GPU) is especially relevant for workloads that depend on low latency, sustained bandwidth, deterministic processing, and custom dataflow. It also explores why FPGAs are gaining renewed attention as system designers look for alternatives and complements to GPU-centric architectures. FPGA vs GPU Interview – Key Insights from the Conference During the session, Mr. Weintraub emphasized that the traditional view of FPGAs as “hard to program” is rapidly changing. With improved toolchains, modular IP libraries, and higher-level development frameworks, FPGAs are becoming far more accessible. This shift allows developers to target workloads that benefit from FPGA architectures. Key advantages can include deterministic latency, custom dataflow, and direct high-bandwidth I/O. One major topic discussed was memory bandwidth. GPUs achieve high throughput, but they are often limited by fixed memory hierarchies. FPGAs, on the other hand, allow developers to build data pipelines tailored to the exact processing flow. As a result, FPGA pipelines can reduce unnecessary data movement and lower latency. They can also handle workloads that benefit from customized dataflow. Where FPGAs Can Outperform GPUs FPGA vs GPU Architecture Comparison Area FPGA GPU Processing Model Custom hardware pipelines and dataflow Programmable massively parallel compute Latency Highly deterministic and predictable Typically more dependent on scheduling and shared resources Streaming Workloads Strong fit for continuous pipelined processing Strong for massively parallel and batched processing I/O Integration Direct and customizable high-bandwidth interfaces Typically uses fixed host, memory, and peripheral interfaces Parallelism Fine-grained and workload-specific Massive general-purpose parallelism AI Inference Efficient for selected and highly optimized workloads Very strong for broad AI frameworks and model execution Image Preprocessing Well suited to deterministic inline image processing Strong when processing is software-friendly and GPU-resident Power Efficiency Can be very strong for fixed-function and streaming workloads Strong for dense, highly parallel compute workloads Development Model More hardware-oriented, with higher-level tools increasingly available Mature software ecosystem with broad framework support Best Fit Real-time, deterministic, custom-dataflow systems AI, analytics, dense parallel compute, and flexible software workloads Swipe horizontally to view all columns → Streaming and real-time processing – FPGAs can process data as it arrives through deeply pipelined hardware, reducing dependence on batching and software scheduling. Deterministic latency – FPGA pipelines can provide highly predictable timing for applications with strict real-time latency requirements. Vector processing and custom compute engines – The architecture adapts to the workload rather than forcing the workload to adapt to the architecture. Power-efficient custom processing – For suitable streaming and fixed-function workloads, FPGA implementations can provide strong performance per watt. Fine-grained parallelism – Enables massive concurrency tailored to the real-time dataflow. Gidel’s Founder and CTO also explained that many modern applications—such as cybersecurity, video analytics, radar, and real-time AI—require predictable performance. FPGA pipelines can provide deterministic timing through dedicated hardware data paths, while GPU execution typically depends on shared compute, memory, and software scheduling resources. FPGA + GPU: Why the Future Isn’t Either–Or The interview highlights the shifting balance between FPGAs and GPUs. Gidel’s CTO emphasizes that many high-performance systems do not need to choose between them. Instead, the real advantage comes from combining both technologies in the same architecture. The GPU excels at AI inference, analytics, and massively parallel workloads, while the FPGA delivers deterministic capture, high-bandwidth I/O, pre-processing, and sensor-level logic. A major benefit of the FPGA is the ability to build custom hardware algorithms that run at wire speed. These include HDR pipelines, debayering, noise reduction, quality enhancement, region-of-interest extraction, timestamping, multi-stream alignment, real-time compression, and even neural-network pre-processing. Because these operations run directly on the FPGA fabric, they can offload substantial pixel-processing work from the CPU and GPU. This can reduce power, bandwidth, and latency. This hybrid approach is exactly what powers Gidel’s FantoVision Edge AI Systems. FantoVision combines NVIDIA Jetson computing with a Gidel Altera Arria 10 FPGA, creating an integrated edge platform for real-time imaging and AI. In this architecture, the FPGA handles high-bandwidth camera acquisition, low-latency triggering, camera control, preprocessing, and FPGA Image Compression IPs. NVIDIA Jetson handles AI inference, analytics, and application-level processing. Accelerating FPGA Development with ProcVision To simplify and accelerate FPGA development, Gidel provides the ProcVision Suite, a modular vision SDK designed for imaging and high-speed acquisition systems. ProcVision enables developers to build fully customized acquisition and processing flows using Gidel’s InfiniVision and ProcFG architectures. It supports inline ISP, HDR, debayering, noise reduction, and on-FPGA compression engines such as Quality+, Lossless, and JPEG. Developers can insert their own proprietary algorithms directly into the FPGA pipeline, enabling real-time preprocessing and significant offloading of CPU and GPU resources. The suite includes the CertifEye validation environment, which streamlines testing and verification of custom IP. By using ProcVision, teams can deploy FPGA-accelerated imaging pipelines with a more integrated development and validation flow. Scaling to 100+ Cameras with InfiniVision Gidel’s approach scales even further through InfiniVision, the company’s open-FPGA acquisition and synchronization framework. InfiniVision enables distributed imaging systems that can capture, stream, and precisely synchronize 100+ cameras across multiple FantoVision units—maintaining deterministic timing and real-time performance. This type of large-scale synchronization benefits from FPGA-based acquisition and hardware timing rather than relying only on software-level coordination. By combining FPGA determinism, GPU flexibility, ProcVision’s development flow, and InfiniVision’s large-scale synchronization, Gidel demonstrates that the future of many demanding real-time systems is not necessarily FPGA versus GPU, but FPGA + GPU working together. This combination can provide a better-balanced architecture by pairing deterministic high-bandwidth I/O and preprocessing with flexible GPU-based AI processing. Read the Full FPGA vs GPU Interview You can read the full interview on The Next Platform: FPGA vs GPU – Time for a Compute Rematch - Published: 2019-10-24 - Modified: 2026-09-11 - URL: https://gidel.com/fpga-image-processing-certifeye/ - Categories: Technical Articles, Press release - Tags: Embedded Vision, Machine Vision, Embedded AI, FPGA Processing, Image Acquisition Discover how CertifEye accelerates FPGA debugging and image-processing validation by enabling engineers to inject test images, verify FPGA IP, analyze results in real time, and streamline development of complex vision pipelines. How FPGA Debugging Tools Accelerate Image Processing Development CertifEye is one of Gidel’s FPGA debugging tools for image-processing development, allowing engineers to inject, process, and analyze test images in real time. It shortens development cycles for advanced machine vision, broadcast, medical imaging, and multi-sensor systems. FPGA Debugging Tools for Image Processing IP Validation CertifEye provides a complete environment for building, debugging, and validating FPGA image processing IP. Engineers can inject known images or video streams into an FPGA or ISP pipeline, process them in real time, and return the results to the host for visual inspection. This workflow enables early correctness checks, which helps teams identify issues long before full system integration. Conventional FPGA Image-Processing Validation vs CertifEye Area Conventional Image-Processing Validation CertifEye Workflow Test Image Injection May require a custom image-source or system-level test setup Known images and video streams can be injected directly into the processing pipeline Debug Cycle Longer compile, deploy, and test iterations Faster iterative validation of FPGA image-processing IP Result Analysis May require custom capture, analysis, or system-level integration Processed results can be returned to the host for immediate visual inspection Repeatability Test conditions may vary between runs Controlled and repeatable image sources improve validation consistency IP Validation Often performed later in system integration Image-processing IP can be verified earlier in the development cycle FPGA Size During Development Often tied to the final target device Algorithms can be debugged on a smaller FPGA before the final target build Development Risk Problems may surface later during system integration Earlier verification helps reduce late-stage redesign risk Swipe horizontally to view all columns → Because the tests are repeatable, teams gain predictable and stable outcomes. As a result, image-processing pipelines become easier to refine and validate. Using CertifEye for FPGA Image Processing Workflows CertifEye integrates with the ProcVision Suite, Gidel’s modular development environment for FPGA-based imaging and ISP pipelines. Developers can work in C/C++, tune parameters with macros, and use advanced debug modes to optimize performance. The workflow ensures bit-accurate validation and supports deployment on Gidel hardware or other Altera FPGA devices. Accelerating Debug, Validation, and Compilation The CertifEye FPGA development tool reduces compilation time by up to 50%. Developers can debug their algorithms on a smaller FPGA and generate a final build for the target device later. This approach shortens iteration cycles and lowers development risks, especially in complex FPGA image processing projects. IP vendors also benefit from the ability to demonstrate multiple configurations—such as pixel widths, pixel-per-clock settings, or different FPGA architectures—without rebuilding a full system each time. Supported FPGA Platforms for CertifEye CertifEye supports FPGA image-processing development across Gidel hardware platforms and compatible Altera FPGA devices. Engineers can use CertifEye with Gidel Mini FPGA Modules, PCIe Frame Grabbers, Mini Edge AI Systems and other Gidel FPGA development platforms based on Altera FPGA devices. This allows developers to validate image-processing IP within the Gidel ecosystem and then move toward the final target FPGA implementation while preserving the same development and verification workflow. Proven Technology for Demanding Vision Applications Gidel has delivered FPGA-based imaging tools for more than 25 years. CertifEye started as a solution built for a partner with rigorous development demands. Its value quickly expanded to a wider audience working on real-time imaging, high-speed pipelines, and integrated vision systems. Customers frequently report faster time-to-market and more reliable image-processing pipelines, as CertifEye simplifies IP development and prevents costly late-stage redesigns. End-to-End Integration for Image and Vision Systems CertifEye connects with Gidel’s hardware modules, frame grabbers, IP library, and host tools. As a result, engineers can move smoothly from algorithm design to grabbing, FPGA acceleration, and application-level processing—all within a unified workflow. This approach supports industries that depend on deterministic, high-performance FPGA image processing, including robotics, medical devices, autonomous platforms, and industrial inspection. Explore CertifEye here: CertifEye-Dev-Kit-Datasheet. pdf Learn about Gidel’s Imaging and Vision tools: ProcVision Suite - Published: 2019-09-16 - Modified: 2026-09-11 - URL: https://gidel.com/news-cxp-12-frame-grabber-8-link-100gbps/ - Categories: Technical Articles, Press release - Tags: CXP-12, Machine Vision, Image Acquisition, CoaXPress Frame Grabbers, FPGA Compression Gidel introduces a 100Gb/s CoaXPress frame grabber with 8 CXP-12 links, on-board Lossless/JPEG compression, deep buffering, and customizable FPGA processing for high-speed vision systems. Proc1C10N-CXP12 for High-Bandwidth CoaXPress Acquisition Gidel, a technology leader in FPGA-based vision and imaging solutions, today announced the Proc1C10N-CXP12, a new 100Gb/s CoaXPress Frame Grabber with 8 × CXP-12 links Built on Altera FPGA technology. The board delivers up to 100 Gb/s aggregate interface bandwidth and combines deterministic acquisition with on-board Lossless/JPEG Compression and customizable FPGA ISP. Proc1C10N-CXP12 100Gb/s CoaXPress Frame Grabber Feature Proc1C10N-CXP12 Camera Interface 8 × CXP-12 links Aggregate Interface Bandwidth Up to 100 Gb/s Camera Power Power-over-CoaXPress (PoCXP) On-Board Memory Up to 33 GB for deep buffering Image Processing Customizable FPGA ISP and real-time processing Compression On-board Lossless and JPEG compression Processing Performance 500+ MPixels/s per encoder Camera Types Area-scan and line-scan CoaXPress cameras Swipe horizontally to view all columns → Meanwhile, Gidel’s HawkEye-CXP12 provides additional CXP-12 configurations. For projects that do not require full CXP-12 bandwidth, the Proc10A-CXP6 offers a more cost-effective alternative with 8 × CXP-6 links while still supporting deterministic acquisition and on-FPGA processing. 100Gb/s CoaXPress Frame Grabber with On-FPGA Compression The 100 Gb/s Proc1C10N-CXP12 and the broader family support line-scan and area-scan cameras and comply with GenICam. In addition, they utilize Power-over-CoaXPress (PoCXP) and provide up to 33 GB of on-board memory for deep buffering. Together with InfiniVision recording, Gidel’s compact compression engines enable synchronized capture across 100+ cameras/sensors. Furthermore, Gidel’s CoaXPress-12 APIs support parallel processing and recording while compression runs directly on the frame grabber. This can reduce PCIe bandwidth, storage requirements, and CPU/GPU load before data reaches the host. The Proc1C10N-CXP12 acquires directly from high-bandwidth CoaXPress cameras through up to 8 × CXP-12 links, supporting deterministic acquisition for high-resolution, high-frame-rate, and multi-camera imaging systems. “Delivering eight CXP-12 links with on-FPGA processing and on-the-fly compression reduces the number of grabbers and host machines required, as well as total power,” said Ofer Pravda, VP Sales & Marketing at Gidel. “Consequently, the Proc1C10N-CXP12 pushes aggregate throughput to 100 Gb/s, enabling acquisition from top-tier cameras at hundreds of frames per second and cutting cost and footprint in large-scale systems. ” On-FPGA ISP and Compression for CoaXPress Systems Teams can accelerate ISP on the FPGA using their IP with Gidel templates. In addition, they may chooseLosslessor JPEG Compression for offline workflows, reducing data rates. Optimize cost and performance by selecting the affordable 8 × CXP-6 or the higher-end CXP-12 configuration with abundant FPGA logic. ProcVision Suite streamlines integration, auto-generates ASPs, and includes CamSim plus debugging and verification tools. “Camera resolutions and frame rates keep climbing, so bandwidth and deterministic processing become the bottlenecks,” added Reuven Weintraub, Founder & CTO at Gidel. “Therefore, pairing CXP-12 with on-FPGA feature extraction, deep on-board buffering, and selective ROI transfer via ProcFG API reduces PCIe bandwidth and host processing, while our compression engines can further lower data rates without sacrificing quality. ” Availability and Options The Proc1C10N-CXP12 (100 Gb/s) is available now. In addition, complementary choices include HawkEye-CXP12 and the more affordable Proc10A-CXP6 with 8 × CXP-6 links to address different performance, integration, and budget requirements. Finally, for custom needs, Gidel also offers ODM services, from FPGA control and data-flow design to custom ISP. For more information, visit PCIe CoaXPress Frame Grabbers. - Published: 2018-11-06 - Modified: 2026-09-11 - URL: https://gidel.com/jpeg-fpga-compression-ip/ - Categories: Technical Articles, Press release - Tags: Embedded Vision, Machine Vision, FPGA Processing, Image Acquisition, CoaXPress Frame Grabbers, GigE Vision Frame Grabbers, Camera Link Frame Grabbers, FPGA Compression Gidel, a technology leader in FPGA-based Vision and Imaging solutions, today announced a new real-time JPEG Compression IP. This compact solution offers 4× higher throughput utilization and supports virtually unlimited image widths, enabling ultra-low-latency compression for high-bandwidth vision and embedded systems. JPEG FPGA Compression IP for Real-Time Imaging Gidel’s FPGA JPEG compression IP delivers real-time encoding with very low latency, compact FPGA resource usage, and 4× higher throughput utilization than comparable solutions. Designed for high-speed Imaging & Vision systems, it processes image data directly in the FPGA path, reducing the amount of data that must be transferred, stored, or handled downstream. High-Speed FPGA Image Compression Gidel, a long-time leader in FPGA-based Vision and Imaging solutions, has introduced a new real-time JPEG encoder for high-speed and embedded imaging systems. The architecture combines compact FPGA resource usage with high processing performance and supports very wide images, making it suitable for demanding high-resolution pipelines. The encoder processes image data directly on the FPGA and supports selectable quality settings, allowing customers to balance image quality, bandwidth, and storage requirements. It accepts YCbCr input, with optional conversion from RGB, Bayer, or monochrome formats. Designed for High-Bandwidth Imaging Applications The Gidel JPEG Encoder on FPGA targets applications that require real-time compression at high pixel rates. Typical applications include large-format cameras, multi-camera systems, recording systems, broadcasting, surveillance, smart cities, embedded vision, and other high-bandwidth imaging systems. For high-bandwidth camera systems, engineers can implement JPEG compression in the FPGA close to the image source. When engineers integrate the FPGA into a camera or embedded imaging platform, compression can reduce the amount of image data transferred downstream. When an FPGA frame grabber performs JPEG compression after camera acquisition, it can reduce PCIe bandwidth, memory traffic, storage requirements, and host CPU/GPU load while maintaining a real-time FPGA processing pipeline. Gidel’s imaging platforms can combine JPEG compression with acquisition from GigE Vision cameras, CoaXPress cameras, Camera Link cameras, and user-defined protocols. FPGA Compression vs CPU and GPU Compression The location of the JPEG encoder in the imaging architecture affects when image data is compressed and how much uncompressed data must move through the rest of the system. FPGA compression can operate directly in the acquisition and image-processing path before the system transfers the data to host memory. FPGA JPEG Compression vs CPU and GPU Compression Architecture FPGA JPEG Compression CPU Compression GPU Compression Processing Location The FPGA can process and compress image data directly in the acquisition path The host CPU performs the compression The GPU compresses the image after the system transfers the data to GPU-accessible memory Streaming Processing Dedicated hardware pipeline can process image data continuously as it arrives Software processing on general-purpose CPU resources Parallel software processing using GPU resources Uncompressed Host Transfer The FPGA can compress image data before the system transfers it to the host Image data normally reaches host memory before CPU compression The system must transfer image data to GPU-accessible memory before the GPU processes it Host CPU Load Dedicated FPGA logic performs the JPEG encoding JPEG encoding uses CPU processing resources The GPU handles the JPEG processing instead of the CPU Integration with Acquisition Engineers can integrate compression with acquisition, buffering, ISP, ROI, and other FPGA processing The host software pipeline performs compression after acquisition The host/GPU processing pipeline handles the compression System Benefit The FPGA can reduce downstream PCIe, memory, storage, and host-processing requirements The CPU provides flexible software-based JPEG compression The GPU provides parallel compression using available GPU compute resources Swipe horizontally to view all columns → Benefits of Real-Time JPEG Compression According to Ofer Pravda, VP Marketing & Sales at Gidel, real-time compression offers several system-level advantages. The system can store compressed image data during acquisition rather than first storing complete uncompressed images in large memory banks. In addition, compressing images in the FPGA before host transfer can reduce PCIe bandwidth, memory traffic, storage requirements, and host processing load. Gidel designed its FPGA JPEG encoder for streaming image processing with very low latency. Current Gidel specifications include performance beyond 1. 8 GPixels/s for 4:2:2 sampling and latency as low as 130 μs, depending on the implementation and configuration. Customizing the Processing Pipeline with ProcVision Suite The ProcVision Suite provides a modular development environment for customizing Gidel FPGA imaging pipelines. Developers can combine Gidel’s JPEG Compression IP with acquisition, buffering, ISP functions, and their own proprietary FPGA processing algorithms. Using ProcVision Suite, developers can adapt the FPGA acquisition and processing path to customer requirements. This lets developers position compression at the appropriate stage of the imaging pipeline and combine it with customer-specific processing before or after compression. Gidel can also provide part or full customization according to customer specifications. Supported Camera Interfaces and FPGA Platforms ProcVision supports GigE Vision, CoaXPress, Camera Link, MIPI, and user-defined camera interfaces and protocols. The development environment supports Gidel FPGA platforms based on Altera FPGA families. This allows engineers to integrate JPEG compression into different imaging architectures, from compact embedded systems and FantoVision Edge AI systems to PCIe frame grabbers, FPGA modules, and high-performance FPGA accelerator platforms. JPEG Compression Across Gidel FPGA Platforms Gidel supports its JPEG Compression IP across several FPGA platforms, including: PCIe Frame Grabbers FantoVision Edge AI Systems Mini FPGA Modules FPGA Compute Accelerators Depending on the platform and system architecture, engineers can perform JPEG compression alongside acquisition and image processing before transferring the image stream to the host. Gidel’s Image-Processing IP Library The JPEG Compression IP is part of Gidel’s broader FPGA image-processing environment, which combines acquisition, compression, image enhancement, buffering, and customer-specific processing within FPGA-based Imaging & Vision systems. Together with Gidel’s FPGA hardware, development tools, and imaging infrastructure, engineers can integrate the JPEG encoder into complete real-time imaging pipelines for acquisition, processing, recording, and data transfer. See the JPEG Compression IP in Action Gidel demonstrated the FPGA JPEG Compression IP at the VISION show in Stuttgart, Germany, where visitors could view real-time compression demonstrations and evaluate the performance of Gidel’s compression technology. Learn more about Gidel’s FPGA JPEG Compression IP - Published: 2018-06-21 - Modified: 2026-08-21 - URL: https://gidel.com/fpga-reversible-compression-ip/ - Categories: Press release - Tags: Machine Vision, Data Reduction, Data Optimization, Image Acquisition, FPGA Processing, Encoder, HPC, Acceleration, Imaging, CoaXPress, High-Bandwidth, Frame Grabber, Low-Latency, Image Processing, Camera Link, GigE Vision, Frame Grabbers, Lossless Compression Gidel, a technology leader in high-performance accelerators utilizing FPGAs, today announced a new Reversible Compression IP. This breakthrough solution reduces storage needs by 50% while consuming under 0.2 W, delivering real-time 1 GB/sec encoding for HPC and vision systems. The new Gidel FPGA-based reversible compression IP reduces storage needs by over 50%, uses as little as 1% of the FPGA, and consumes under 0. 2 W. This ultra-efficient design enables real-time 1 GB/sec encoding and makes the IP ideal for high-bandwidth, vision, and data-intensive applications. Learn more about Gidel’s reversible compression IP here: Lossless Compression. Why FPGA-Based Reversible Compression Matters Today Renewed focus on compression and encryption IPs Gidel announced its new real-time reversible compression IP for FPGAs, offering a breakthrough combination of speed, efficiency, and ultra-low resource usage. The solution targets the HPC, Vision, and data-center markets—where bandwidth limits, power constraints, and storage requirements are becoming increasingly critical. This new IP enables real-time, mathematically reversible compression—allowing the original data to be perfectly reconstructed with zero degradation. Gidel developed the IP in response to customers requiring much higher performance than commercial software compression formats can deliver. Early evaluations showed superior compression ratios, faster computation time, and dramatically lower power consumption than CPU-based alternatives. Ultra-efficient FPGA reversible compression design (1% FPGA usage) The Gidel FPGA reversible compression core uses only a small number of logic elements and consumes less than 0. 2 W. For example, when running on the HawkEye Arria 10-480 board, the complete IP occupies just 1% of the FPGA silicon. This compact footprint makes it suitable for all Gidel high-performance boards—including FPGA modules and frame grabbers. Real-time reversible compression improves system efficiency on multiple fronts. Data can be stored immediately in compressed form rather than waiting for offline processing. Memory bandwidth is also significantly improved, as less data must be transferred to host memory or SSD storage. Boosting storage efficiency and sensor-based system performance Real-time reversible compression is especially critical for systems capturing large volumes of sensor data in the field. Applications with limited storage capacity or restricted uplink bandwidth benefit immediately. By reducing data size by more than 50%, the IP effectively doubles available capacity, increases sensor count, or increases acquisition speed—depending on system requirements. Initial tests were performed using hundreds of images supplied by Gidel’s strategic partners. The new IP is now available for customer deployments. Part of a broader compression and encryption roadmap Gidel offers multiple compression IPs and is preparing a family of FPGA-based encryption IPs. When deployed together—reversible compression followed by encryption—customers can build efficient and secure pipelines for cloud applications, edge systems, and imaging workflows. Both IP types are available as modular components in the Gidel tools library. This expanded focus on compression and encryption provides strong ROI for customers by reducing power consumption and lowering storage and processing needs. Combined with Gidel’s established vision processing capabilities, the IP family is ideal for applications such as recording systems, mapping, autonomous vehicles, homeland security, and other high-bandwidth workload environments. Gidel presented the reversible compression IP at ISC 2018 in Frankfurt, Germany (booth G-814). Visitors were able to see live demonstrations of the technology. - Published: 2017-11-09 - Modified: 2026-03-05 - URL: https://gidel.com/fpga-acceleration-chrec-supercomputer/ - Categories: Case Studies - Tags: Low-Latency, HPC, Super Computing, CHREC, FPGA Acceleration, NOVO-G Discover how CHREC utilized Gidel’s FPGA acceleration technology to build Novo-G, the world’s fastest research-focused reconfigurable supercomputer. Learn how our direct FPGA-to-FPGA connectivity enables massive parallelism, ultra-low latency, and superior power efficiency for HPC clusters. The new FPGA acceleration technology from Gidel enables ultra-low-latency, full-duplex connectivity for reconfigurable supercomputers. This capability allows HPC researchers to design flexible, power-efficient clusters using direct FPGA-to-FPGA links with no CPU overhead. Learn more about Gidel’s FPGA Acceleration cards: Gidel FPGA Accelerators. Read more about reconfigurable computing research at CHREC: National Science Foundation. Gidel FPGA Acceleration for Reconfigurable HPC Systems Data centers face exponential data growth and increasing power demands. Traditional CPU-based architectures struggle to scale without major increases in power and cooling. Gidel’s FPGA acceleration technology provides a high-performance alternative, offering massive parallelism with significantly lower power consumption. Gidel’s direct FPGA connectivity replaces CPU involvement entirely, enabling real-time computation across FPGA clusters. This connectivity supports advanced topologies such as 3D and 12D Torus, and 6D or 24D Hypercube, making it ideal for HPC workloads that require extreme throughput. CHREC Builds a Reconfigurable Supercomputer Using Gidel FPGA Boards The Center for High Performance Reconfigurable Computing (CHREC), funded by the National Science Foundation, set out to create the fastest research-focused reconfigurable supercomputer in the world. Their goal was to evaluate architectures that deliver both high performance and low energy consumption. Initially, CHREC researchers explored CPU-socket accelerators but encountered instability, high costs, and under-performing I/O bandwidth. They shifted toward PCIe FPGA boards and evaluated multiple vendors. After extensive testing, Gidel was selected for its performance, stability, and superior technical support. Why Gidel Was Chosen for the Novo-G Supercomputer Highest FPGA speed grades available at the time Best-in-class FPGA-to-host and FPGA-to-FPGA throughput Large on-board memory with low latency Mature API and run-time environment for rapid development The resulting system, called Novo-G, used hundreds of Gidel FPGA cards (ProcStar III/IV and ProceV D8). These cards were interconnected using Gidel’s direct FPGA links, forming a high-speed 3D torus network that enabled FPGA-to-FPGA computation without CPU involvement. 2×4×4 Torus configuration (expandable) Record-Setting FPGA Acceleration Performance The Novo-G cluster delivered performance thousands of times more power-efficient than conventional supercomputers. It won the 2012 Alexander Schwarzkopf Prize for technology innovation and demonstrated nearly double the performance of Anton and fifty times the performance of BlueGene/L on the 3D FFT kernel. This success validated Gidel’s approach to high-throughput, low-latency FPGA acceleration for large-scale HPC infrastructure. Long-Term Collaboration and Scalable Architecture Gidel and the CHREC team have collaborated for more than a decade. According to the researchers, migrating between Gidel FPGA platforms was straightforward because the hardware architecture and API remained consistent across generations. The design supports scalability. One Gidel FPGA board can manage a large multi-dimensional communication network, and additional nodes can be added seamlessly to expand the cluster. - Published: 2017-11-03 - Modified: 2026-06-17 - URL: https://gidel.com/360-degree-camera-system/ - Categories: Case Studies - Tags: Low-Latency, infiniVision, Acceleration, FPGA, Intel Sport, AR, VR, MIPI, 360-degree camera system, Image Acquisition Discover how Gidel’s InfiniVision technology powers next-gen VR with a fully synchronized 24-camera array. Learn how our scalable FPGA architecture delivers seamless 360-degree imaging through precise timing, custom backplanes, and high-bandwidth fiber-optic transmission for next generation immersive fan experiences across media, sports, and entertainment. Gidel’s InfiniVision technology enables a complete 360-degree camera system for VR and AR applications. It allows developers to capture synchronized, high-quality images from large camera arrays and create immersive panoramic content for next-generation media, sports, and interactive experiences. Learn more about Gidel InfiniVision. Watch the demonstration here: InfiniVision Example. 360 Degree Camera System Built with Gidel InfiniVision A leading semiconductor company selected Gidel to help develop a highly scalable 360-degree camera system for its VR product division. The system captures panoramic content using 24 synchronized MIPI sensors. Intel, acting as a technology advisor to the customer, recommended Gidel because of its strong expertise in FPGA-based imaging and vision systems. To support this project, Gidel designed a custom FPGA I/O card that enables simultaneous acquisition from all 24 cameras. This infrastructure allows the semiconductor company to generate high-resolution VR content with precise control over timing, exposure, and sensor behavior. FPGA Architecture for 360 Degree Camera Arrays Each Gidel FPGA I/O card supports up to six MIPI cameras. Therefore, the full solution uses four synchronized cards to capture the entire 24-camera array. This modular design makes the system scalable, flexible, and easy to adapt to new VR or AR devices. Furthermore, Gidel’s hardware handles frame aggregation and timing alignment. As a result, the system maintains strict synchronization across all cameras—an essential requirement for stitching accurate 360-degree images. Synchronized Capture for 360 Degree Imaging Gidel’s FPGA technology ensures that every camera in the array operates with matching exposure timing, white balance, color processing, and gamma correction. This alignment dramatically improves stitching quality and reduces image mismatches during panoramic reconstruction. Additionally, the FPGA I/O cards manage camera enumeration, initialization, and control operations. Developers gain predictable, deterministic behavior for all 24 sensors, which is crucial for real-time VR pipelines. Software API for Full Camera-Array Control Alongside the hardware, Gidel created a dedicated software API that exposes system-level control to application developers. The API simplifies tasks such as camera reset, initialization, frame synchronization, and data handling. Consequently, software teams can integrate the solution into larger VR/AR platforms without needing FPGA expertise. This combination of FPGA hardware, real-time acquisition, and a flexible software API delivers an end-to-end imaging pipeline that is extremely difficult to achieve using conventional architectures. Download the InfiniVision Datasheet (PDF) ## Products - Published: 2025-12-29 - Modified: 2026-07-17 - URL: https://gidel.com/product/skyboost-fastest-raw-to-jpg-acceleration/ - Product categories: FPGA Compute Acceleration Boards, Modular Imaging Solutions, GIL: FPGA Imaging Libraries (IPs), Aerial Mapping ISP: SkyBoost-RT vs. SkyBoost Product Overview SkyBoost is a workstation-grade acceleration solution designed to eliminate post-processing bottlenecks by performing high-volume and high quality RAW to JPG conversion using a dedicated hardware accelerator. Unlike standard software that relies on CPU or GPU processing, this platform ensures rapid batch processing for Aerial Mapping, Orthophoto, and Large-Scale Inspection—especially when utilizing High-Resolution Sensors (HRS) in demanding Outdoor Imaging environments. By massively reducing the processing time per image, the solution processes terabytes of aerial imagery in less than an hour. It converts massive "data dumps" from flight missions into ready-to-use imagery at speeds 50x faster than standard market solutions. Solving the RAW to JPG Backlog In high-end aerial surveying, the challenge shifts from the aircraft to the office the moment the drone lands. A single flight can generate thousands of high-resolution RAW files, creating a massive data backlog. Standard software tools like Capture One™ or RawTherapee are excellent for interactive editing but struggle to handle this industrial scale, often tying up workstations for days. SkyBoost addresses these challenges by offloading the conversion to a dedicated hardware engine: The system performs Batch Processing of High-Resolution RAW (Bayer) data stored on local drives. FPGA-based ISP enhances image quality identically to high-end camera pipelines. Hardware acceleration delivers performance more than 50x faster than software-based conversion. Reduces project turnaround time from days to minutes (or hours for massive datasets). Furthermore, this approach frees up your standard workstations for other tasks, as the heavy lifting is handled entirely by the SkyBoost accelerator card. Performance at Scale Sensor Class Processing Speed Throughput 100 MP > 3 FPS > 1 Terapixel / Hour 150 MP > 2 FPS > 1 Terapixel / Hour Swipe horizontally to view all columns → *Throughput values depend on specific pixel format and system configuration. High Quality RAW to JPG Pipeline Optimized for Aerial Imaging An FPGA-based image processing pipeline optimized for aerial imaging performs all stages deterministically to ensure maximum quality. Specifically, the pipeline includes: Demosaicing – Converts raw Bayer data into sharp, full-color RGB imagery High Dynamic Range (HDR) – Captures superior details in high-contrast lighting conditions Chromatic Aberration Correction – Corrects color fringing and lens-related color misalignments for crisper edges Non-Uniformity Correction (NUC) – Calibrates individual pixel responses to ensure a uniform image across the entire sensor Bad Pixel Replacement (BPR) – Automatically identifies and compensates for defective pixels in real time Dynamic Luminance Balance – Preserves consistent brightness under changing illumination White Balance – Maintains color accuracy across variable lighting conditions High-Speed JPG compression exceeding a 10:1 ratio directly on the FPGA. All processing stages operate with high-throughput buffering, ensuring stable performance even when processing massive folders of high-resolution imagery. High-Throughput RAW to JPG Conversion The architecture handles ultra-high-resolution sensors, supporting image widths of up to 32K pixels. This corresponds to cameras of up to ~500MP, ensuring compatibility with the most advanced mapping sensors. In high-volume batch workflows, the system can process over 3 images per second. Deployment on Workstations and Edge Systems SkyBoost is designed for easy integration into existing IT infrastructure via PCIe FPGA Accelerator cards or Embedded Edge Computers. This makes it the ideal engine for processing massive aerial imaging datasets across two primary deployment formats: PCIe FPGA Accelerator cards – Installed in standard office workstations or servers Embedded Edge Computers – Standalone units ISP Customization for RAW Image Processing The ProcVision SDK provides full control over the Image Signal Processing pipeline through FPGA-level customization. This enables application-specific ISP design to meet precise imaging requirements. Additionally, the system calibrator handles pipeline optimization, allowing configuration of the processing flow to balance image quality, compression ratio, and throughput based on the specific needs of the mapping project. Why Choose SkyBoost for Your Data Workflow? SkyBoost transforms the economics of aerial mapping by virtually eliminating the processing "wait time". By processing > 1 Terapixel / Hour, it allows you to deliver orthophotos and 3D models to clients faster than ever before. It provides the industrial speed required to match the industrial volume of modern aerial sensors. Looking for On-the-Fly processing? See SkyBoost-RT. - Published: 2025-12-29 - Modified: 2026-07-13 - URL: https://gidel.com/product/skyboost-rt-aerial-imaging/ - Product categories: FantoVision20 Edge AI with FPGA Frame Grabbers, GigE Vision Frame Grabbers & Image Processing, CoaXPress Frame Grabbers & Image Processing, Frame Grabbers & Image Processing, Camera Link Frame Grabbers & Image Processing, Mini FPGA Modules, Modular Imaging Solutions, Development Tools for Imaging & Vision Applications, FPGA Image Compression IPs, GIL: FPGA Imaging Libraries (IPs), Low Latency Recording & Streaming Solutions, Image Acquisition Solutions: ProcFG vs InfiniVision, Aerial Mapping ISP: SkyBoost-RT vs. SkyBoost, FantoVision40 Edge AI with FPGA Frame Grabbers Product Overview SkyBoost-RT is a dedicated solution for real-time aerial imaging and similar applications, designed to accelerate End-to-End processing directly on mission-critical airborne platforms. It enables High-Quality on-the-fly Image Signal Processing (ISP) and compression while the HRS is actively capturing RAW data, allowing high-quality imagery to be processed, recorded, or streamed in real time for Military & Defense ISR, Search & Rescue, and Situational Awareness. Built for pipelines where deterministic behavior, low latency, and continuous operation are critical, the solution processes and compresses RAW image data immediately during acquisition. This ensures seamless data flow without buffering delays or the need for intensive post-processing. Solving Data Bottlenecks in Aerial Imaging In many airborne systems, storing or transferring uncompressed RAW image data is not practical. High-resolution sensors (HRS) quickly generate terabytes of data, creating significant challenges for storage capacity, bandwidth, and real-time usability. SkyBoost-RT addresses these challenges by performing image processing and compression on the fly: The system processes High-Resolution RAW (Bayer) image data in real time while the camera is filming FPGA-based ISP enhances image quality before compression JPG compression significantly reduces data volume during acquisition, often exceeding a 10:1 compression ratio Deterministic behavior ensures continuous operation without dropped frames Furthermore, this approach enables long-duration recording without accumulating massive storage requirements and makes real-time streaming substantially easier due to the reduced data bandwidth. High-Quality Processing Pipeline Optimized for Aerial Imaging An FPGA-based image processing pipeline optimized for aerial imaging and real-time operation performs all stages deterministically. Specifically, the pipeline includes: Demosaicing – Converts raw Bayer data into sharp, full-color RGB imagery High Dynamic Range (HDR) – Captures superior details in high-contrast lighting conditions Chromatic Aberration Correction – Corrects color fringing and lens-related color misalignments for crisper edges Non-Uniformity Correction (NUC) – Calibrates individual pixel responses to ensure a uniform image across the entire sensor Bad Pixel Replacement (BPR) – Automatically identifies and compensates for defective pixels in real time Dynamic Luminance Balance – Preserves consistent brightness under changing illumination White Balance – Maintains color accuracy across variable lighting conditions JPG compression exceeding a 10:1 ratio directly on the FPGA Optional: H. 264 / H. 265 – Industry-standard video compression for efficient recording and transmission RTSP Output Options – Enables bandwidth-efficient video streaming and recording All processing stages operate with controlled buffering and predictable latency, ensuring stable performance under sustained high data rates. Throughput for High-Resolution Aerial Sensors (HRS) The architecture is purpose-built for Ultra-Aerial-HRS, supporting image widths of up to 32K pixels. This corresponds to cameras of up to ~500MP, depending on the model and configuration. In real-time pipelines, the system can process over 7 images per second, depending on configuration and input format. Additionally, it sustains high frame rates even at very large frame sizes, enabling continuous acquisition, processing, and compression without interrupting the image stream. Performance at Scale Sensor Class Processing Speed Throughput 100 MP > 7 FPS > 2 Terapixels / Hour 150 MP > 4. 5 FPS > 2 Terapixels / Hour Swipe horizontally to view all columns → *Throughput values depend on specific pixel format and system configuration. Deployment on Airborne and Embedded Platforms Gidel supports deployment across multiple hardware platforms, depending on system architecture and operational constraints: Mini Jetson Frame Grabber Systems combining FPGA acceleration with embedded GPU processing FPGA Frame Grabbers installed in user PCs or servers FPGA modules for compact, embedded, and low-SWaP deployments This makes the solution particularly well suited for platforms where size, weight, and power matter, such as embedded airborne systems, compact payloads, and the broader aerial imaging environment. Supported Interfaces The system supports a wide range of high-end camera and sensor interfaces, including: 1-10 GigE Vision CoaXPress-12 and CoaXPress-6 All Camera Link configurations Custom user-defined protocols ISP Customization for UAV and Aerial Systems The ProcVision SDK provides full control over the Image Signal Processing pipeline through FPGA-level customization. This enables application-specific ISP design to meet precise imaging requirements. Additionally, the system calibrator handles pipeline optimization, allowing configuration of the processing flow to balance image quality, compression ratio, throughput, and system resource utilization. Why Choose SkyBoost-RT for Your Aerial Imaging Application? SkyBoost-RT overcomes the storage and bandwidth limitations of airborne platforms by processing and compressing massive RAW data streams in real time, ensuring you capture all images without overwhelming your downlink. It empowers mission-critical ISR and inspection operations with immediate visual intelligence, all within the tight power and weight limits of modern UAVs. Need to accelerate your workflow back at the office instead? Discover SkyBoost to drastically reduce your post-processing times. - Published: 2025-12-24 - Modified: 2026-03-31 - URL: https://gidel.com/product/image-acquisition-system-procfg/ - Product categories: FantoVision20 Edge AI with FPGA Frame Grabbers, Products, GigE Vision Frame Grabbers & Image Processing, CoaXPress Frame Grabbers & Image Processing, Frame Grabbers & Image Processing, Camera Link Frame Grabbers & Image Processing, Mini FPGA Modules, Modular Imaging Solutions, Development Tools for Imaging & Vision Applications, GIL: FPGA Imaging Libraries (IPs), Image Acquisition Solutions: ProcFG vs InfiniVision ProcFG: Deterministic Image Acquisition System ProcFG is Gidel’s deterministic image acquisition system, engineered to reliably capture every frame produced by connected cameras without loss. The system targets Machine Vision & Imaging applications that demand predictable timing, complete data integrity, and long-term operational stability. Unlike flexible multi-camera platforms that favor dynamic configurations, ProcFG enforces strict acquisition rules in hardware, preventing frame drops caused by host CPU contention or operating system scheduling. Acquisition Architecture for Guaranteed Frame Capture ProcFG operates as an acquisition application on top of Gidel’s FPGA-based frame grabbers. It controls how the system captures, buffers, and delivers image data to the host. Its primary goal is to prevent frame loss during continuous operation. ProcFG handles acquisition logic directly on the FPGA. This approach minimizes reliance on host-side software timing. As a result, downstream pipelines receive a complete and ordered image stream, even in high-throughput or long-duration deployments. ProcFG integrates seamlessly with Gidel PCIe Frame Grabbers. It can also run on Mini Jetson Frame Grabber Systems and FPGA Modules for compact or embedded installations. The platform works with GigE Vision, CoaXPress, and Camera Link interfaces. Gidel can also add custom sensor interfaces and protocols on request. Deterministic Image Acquisition Model and Operating Variants ProcFG uses a deterministic acquisition model. The system defines frame size, pixel format, and timing behavior in hardware. This approach simplifies system validation and reduces variability across operating conditions. ProcFG offers multiple variants to address specific acquisition needs. These include single-camera and multi-camera setups that require strict timing alignment and repeatable behavior. Designers can select the right balance between throughput, buffering, and synchronization without risking frame integrity. FPGA-Based Image Acquisition Preprocessing and Data Handling In addition to frame capture, ProcFG performs FPGA-based preprocessing directly on the frame grabber. Processing data close to the sensor reduces unnecessary data movement and lowers host-side load. ProcFG can also include optional inline processing blocks such as ISP. These blocks help manage bandwidth, storage, and processing efficiency while preserving deterministic acquisition behavior. Integration into Gidel Vision Architectures ProcFG integrates naturally into Gidel’s broader vision ecosystem. It serves as the deterministic acquisition layer within systems that also include FPGA-based image enhancement or embedded processing. Some applications require flexible camera configurations, dynamic frame sizes, or very large synchronized camera arrays. For these cases, Gidel offers the InfiniVision multi-camera vision system. ProcFG is the preferred choice when guaranteed frame capture and predictable behavior matter more than flexibility. Why Choose the ProcFG ProcFG provides a focused and reliable foundation for deterministic vision systems. It moves acquisition control into FPGA hardware and enforces strict capture behavior. This approach enables complete and repeatable image acquisition under sustained load. When frame integrity, timing predictability, and long-term stability are critical, ProcFG delivers a proven and purpose-built image acquisition system. - Published: 2025-10-01 - Modified: 2026-08-14 - URL: https://gidel.com/product/octo-cxp-12-frame-grabber/ - Software Types: Imaging & Vision - Product categories: CoaXPress Frame Grabbers & Image Processing, Frame Grabbers & Image Processing, Modular Imaging Solutions, FPGA Image Compression IPs, GIL: FPGA Imaging Libraries (IPs), Low Latency Recording & Streaming Solutions, Image Acquisition Solutions: ProcFG vs InfiniVision 8-Link CXP-12 Frame Grabber for CoaXPress Cameras The Proc1C10N-CXP12 is a high-performance eight-link CXP-12 frame grabber designed for real-time image acquisition, preprocessing, compression, and AI acceleration from high-speed CoaXPress-12 cameras in demanding multi-camera vision systems. Built on Gidel’s Proc10N FPGA module with Altera Stratix 10 NX FPGA technology, it integrates embedded Tensor Blocks and HBM2 memory, delivering up to 143 INT8 TOPS of AI processing performance. As a result, it can process and analyze data from up to 8 × CXP-12 links, making it ideal for advanced vision-based AI systems. Octo CXP-12 Acquisition with Real-Time FPGA Image Processing The Proc1C10N-CXP12 is available as a plug-and-play CXP frame grabber or as part of a complete imaging & vision system with real-time FPGA preprocessing, image enhancement, and compression options. The built-in FPGA can process image data during acquisition, before it reaches the host PC. This helps reduce bandwidth, storage, and host processing load while preserving low-latency performance for high-speed camera streams. Optional FPGA processing includes Compression, HDR correction, Detection, and additional image enhancement modules. Real-Time FPGA Processing Helps Enable: Reduced bandwidth for high-throughput image acquisition Low-latency processing directly in the acquisition flow Extended recording time through real-time compression Lower host processing load by offloading selected tasks to the FPGA Custom image pipelines using Gidel IPs or user FPGA logic For the full list of available image processing and enhancement options, please refer to the Options tab. Flexible Operating Modes The Proc1C10N-CXP12 supports two operating modes selectable via firmware: InfiniVision: Designed for synchronized multi-camera setups, combining all camera data, including data acquired across multiple cards, into a single buffer with support for dynamic resolutions and formats. ProcFG: Tailored for precision and line-scan applications, offering fixed frame sizes, pixel formats, and uncompressed ROI grabbing. As a result, the Proc1C10N-CXP12 adapts to diverse workflows, supporting both complex multi-camera systems and single-camera applications requiring consistent, high-performance acquisition. InfiniVision: Multi-Camera Acquisition and Synchronization Built on Gidel’s InfiniVision architecture, the Proc1C10N-CXP12 addresses key multi-camera challenges, including synchronization, bandwidth, connectivity, and scalability. It supports up to eight CXP-12 links, enabling simultaneous acquisition from one to eight cameras, depending on the number of links required by each camera. A PCIe Gen3 x16 host interface provides ultra-fast data transfer, while on-board HBM2 and DDR4 memory help sustain acquisition and real-time FPGA processing under demanding loads. As a result, the Proc1C10N-CXP12 delivers reliable performance in high-bandwidth, AI-driven imaging systems. SDK and Development Tools The Proc1C10N-CXP12 is supported by Gidel’s SDK, featuring intuitive GUIs and APIs for easy integration. Moreover, the ProcVision Suite adds advanced FPGA programming, debugging, and validation tools, enabling rapid customization of data pipelines, real-time processing, and compression workflows—so teams can deploy optimized, application-specific solutions faster and with reduced risk. Why Choose the Proc1C10N-CXP12 Frame Grabber? Eight-link CXP-12 FPGA frame grabber for high-speed multi-camera image acquisition Up to 100 Gb/s aggregate input bandwidth Embedded AI Tensor Blocks for acceleration and inference Flexible operating modes for multi-camera and precision setups Advanced SDK and ProcVision Suite for rapid development and integration Optional real-time FPGA processing, image enhancement, and compression IPs The Proc1C10N-CXP12 is the ideal choice when your workload requires high-bandwidth CXP-12 acquisition, deterministic multi-camera capture, and FPGA-based acceleration for AI-driven imaging workflows. Related ProductsView the Full Range of PCIe CoaXPress Frame Grabbers View the FantoVision40-CXP12: Edge AI CoaXPress System View the CoaXPress Camera Simulator - Published: 2025-09-08 - Modified: 2026-08-14 - URL: https://gidel.com/product/jetson-gige/ - Software Types: FantoVision20 - Product categories: FantoVision20 Edge AI with FPGA Frame Grabbers, GigE Vision Frame Grabbers & Image Processing, Modular Imaging Solutions, FPGA Image Compression IPs, GIL: FPGA Imaging Libraries (IPs), Low Latency Recording & Streaming Solutions, Image Acquisition Solutions: ProcFG vs InfiniVision, Aerial Mapping ISP: SkyBoost-RT vs. SkyBoost, FantoVision Edge AI with FPGA Frame Grabbers Jetson with Dual 10 GigE Vision Frame Grabber The FantoVision20-GigE is a rugged Jetson system with a fully integrated GigE Vision frame grabber. Powered by the NVIDIA Jetson Orin NX or Xavier NX, it captures and processes data from up to 2 × 10 GigE Vision cameras in real time. It combines high-end image acquisition on an Arria 10™ FPGA with real-time GPU processing on Jetson, enabling low-latency recording, streaming, and Edge AI in an ultra-compact, low-SWaP form factor. Jetson GigE Vision Acquisition with Real-Time FPGA Image Processing The FantoVision20-GigE is available as a plug-and-play GigE frame grabber system or as part of a complete Imaging & Vision solution with real-time FPGA preprocessing, image enhancement, and compression options. The built-in FPGA can process image data during acquisition, before the data reaches the Jetson module. This helps reduce bandwidth, storage, and Jetson processing load while preserving low-latency performance for high-speed camera streams. Optional FPGA processing includes Compression, HDR correction, Detection, and additional image enhancement modules. Real-Time FPGA Processing Helps Enable: Reduced bandwidth for high-throughput image acquisition Low-latency processing directly in the acquisition flow Extended recording time through real-time compression Lower Jetson processing load by offloading selected tasks to the FPGA Custom image pipelines using Gidel IPs or user FPGA logic For the full list of available image processing and enhancement options, please refer to the Options tab. Flexible Development Tools Open architecture: split/chain processing between FPGA and GPU GPU development: CUDA | C/C++ and NVIDIA AI libraries on Jetson FPGA development: rapid pre‑processing deployment with ProcVision Suite Integrated Vision Acquisition and Processing Deploy a single compact Jetson + FPGA node for GigE camera acquisition, real-time preprocessing, Edge AI inference, recording, and streaming. This approach reduces cabling, latency, and overall system cost while improving reliability and maintainability. For large-scale, synchronized camera deployments, Gidel’s InfiniVision multi-camera vision system enables synchronization and processing across 100+ sensors within a flexible acquisition framework. For applications that require strict determinism, line-scan optimization, or guaranteed frame capture with fixed timing, ProcFG provides a dedicated deterministic image acquisition layer. Both approaches integrate seamlessly into Gidel’s FPGA-based vision platforms and scale from single-node systems to multi-unit topologies. Why Choose the FantoVision20‑GigE? Compact NVIDIA Jetson + FPGA system with integrated Dual 10 GigE Vision frame grabber Up to 20 Gb/s aggregate input bandwidth FPGA + GPU architecture for low-latency acquisition, processing, recording, streaming, and Edge AI Optional real-time FPGA image processing, enhancement, and compression IPs The FantoVision20-GigE is the ideal choice when you need high-speed GigE Vision camera acquisition in a compact, low-latency Jetson platform. Related ProductsView the Full FantoVision System Range View the Full Range of PCIe GigE Vision Frame Grabbers - Published: 2025-09-08 - Modified: 2026-08-14 - URL: https://gidel.com/product/jetson-coaxpress/ - Software Types: FantoVision40 - Product categories: CoaXPress Frame Grabbers & Image Processing, Modular Imaging Solutions, Development Tools for Imaging & Vision Applications, FPGA Image Compression IPs, GIL: FPGA Imaging Libraries (IPs), Low Latency Recording & Streaming Solutions, Image Acquisition Solutions: ProcFG vs InfiniVision, Aerial Mapping ISP: SkyBoost-RT vs. SkyBoost, FantoVision40 Edge AI with FPGA Frame Grabbers, FantoVision Edge AI with FPGA Frame Grabbers Jetson with Quad CoaXPress-12 Frame Grabber The FantoVision40-CXP12 is a rugged Jetson system with a fully integrated CoaXPress-12 frame grabber. Powered by the NVIDIA Jetson Orin NX, it captures and processes data from up to 4 × CoaXPress CXP-12 links in real time with PoCXP. It combines high-end image acquisition on an Arria 10™ FPGA with real-time GPU processing on Jetson, enabling low-latency recording, streaming, and Edge AI in an ultra-compact, low-SWaP form factor. Jetson CXP-12 Acquisition with Real-Time FPGA Image Processing The FantoVision40-CXP12 is available as a plug-and-play CXP frame grabber system or as part of a complete imaging & vision solution with real-time FPGA preprocessing, image enhancement, and compression options. The built-in FPGA can process image data during acquisition, before the data reaches the Jetson module. This helps reduce bandwidth, storage, and Jetson processing load while preserving low-latency performance for high-speed camera streams. Optional FPGA processing includes Compression, HDR correction, Detection, and additional image enhancement modules. Real-Time FPGA Processing Helps Enable: Reduced bandwidth for high-throughput image acquisition Low-latency processing directly in the acquisition flow Extended recording time through real-time compression Lower Jetson processing load by offloading selected tasks to the FPGA Custom image pipelines using Gidel IPs or user FPGA logic For the full list of available image processing and enhancement options, please refer to the Options tab. Flexible Development Tools Open architecture: split/chain processing between FPGA and GPU GPU development: CUDA | C/C++ and NVIDIA AI libraries on Jetson FPGA development: rapid pre‑processing deployment with ProcVision Suite Integrated Vision Acquisition and Processing Deploy a single compact Jetson + FPGA node for CXP camera acquisition, real-time preprocessing, Edge AI inference, recording, and streaming. This approach reduces cabling, latency, and overall system cost while improving reliability and maintainability. For large-scale, synchronized camera deployments, Gidel’s InfiniVision multi-camera vision system enables synchronization and processing across 100+ sensors within a flexible acquisition framework. For applications that require strict determinism, line-scan optimization, or guaranteed frame capture with fixed timing, ProcFG provides a dedicated deterministic image acquisition layer. Both approaches integrate seamlessly into Gidel’s FPGA-based vision platforms and scale from single-node systems to multi-unit topologies. Why Choose the FantoVision40‑CXP12? Compact NVIDIA Jetson + FPGA system with integrated Quad CXP-12 frame grabber PoCXP support for long-reach, robust camera connectivity Up to 50 Gb/s aggregate CXP-12 link bandwidth FPGA + GPU architecture for low-latency acquisition, processing, recording, streaming, and Edge AI Optional real-time FPGA image processing, enhancement, and compression IPs The FantoVision40-CXP12 is the ideal choice when you need high-throughput CoaXPress-12 camera acquisition in a compact, low-latency Jetson platform. Related ProductsView the Full FantoVision System RangeView the Full Range of PCIe CoaXPress Frame Grabbers View the CoaXPress Camera Simulator - Published: 2025-09-07 - Modified: 2026-08-14 - URL: https://gidel.com/product/jetson-camera-link/ - Software Types: FantoVision20 - Product categories: FantoVision20 Edge AI with FPGA Frame Grabbers, Camera Link Frame Grabbers & Image Processing, Modular Imaging Solutions, Development Tools for Imaging & Vision Applications, FPGA Image Compression IPs, GIL: FPGA Imaging Libraries (IPs), Low Latency Recording & Streaming Solutions, Image Acquisition Solutions: ProcFG vs InfiniVision, Aerial Mapping ISP: SkyBoost-RT vs. SkyBoost, FantoVision Edge AI with FPGA Frame Grabbers Jetson with Camera Link Frame Grabber The FantoVision20-CL is a rugged Jetson system with a fully integrated Camera Link frame grabber. Powered by the NVIDIA Jetson Orin NX or Xavier NX, it captures and processes data from Camera Link Deca, Full, Medium, Base, and Dual Base camera configurations in real time. It combines high-end image acquisition on an Arria 10™ FPGA with real-time GPU processing on Jetson, enabling low-latency recording, streaming, and Edge AI in an ultra-compact, low-SWaP form factor. Jetson Camera Link Acquisition with Real-Time FPGA Image Processing The FantoVision20-CL is available as a plug-and-play Camera Link grabber system or as part of a complete Imaging & Vision solution with real-time FPGA preprocessing, image enhancement, and compression options. The built-in FPGA can process image data during acquisition, before the data reaches the Jetson module. This helps reduce bandwidth, storage, and Jetson processing load while preserving low-latency performance for high-speed camera streams. Optional FPGA processing includes Compression, HDR correction, Detection, and additional image enhancement modules. Real-Time FPGA Processing Helps Enable: Reduced bandwidth for high-throughput image acquisition Low-latency processing directly in the acquisition flow Extended recording time through real-time compression Lower Jetson processing load by offloading selected tasks to the FPGA Custom image pipelines using Gidel IPs or user FPGA logic For the full list of available image processing and enhancement options, please refer to the Options tab. Flexible Development Tools Open architecture: split/chain processing between FPGA and GPU GPU development: CUDA | C/C++ and NVIDIA AI libraries on Jetson FPGA development: rapid pre‑processing deployment with ProcVision Suite Integrated Vision Acquisition and Processing Deploy a single compact Jetson + FPGA node for Camera Link acquisition, real-time preprocessing, Edge AI inference, recording, and streaming. This approach reduces cabling, latency, and overall system cost while improving reliability and maintainability. For large-scale, synchronized camera deployments, Gidel’s InfiniVision multi-camera vision system enables synchronization and processing across 100+ sensors within a flexible acquisition framework. For applications that require strict determinism, line-scan optimization, or guaranteed frame capture with fixed timing, ProcFG provides a dedicated deterministic image acquisition layer. Both approaches integrate seamlessly into Gidel’s FPGA-based vision platforms and scale from single-node systems to multi-unit topologies. Why Choose the FantoVision20-CL? Compact NVIDIA Jetson + FPGA system with integrated Camera Link frame grabber Up to 6. 8 Gb/s aggregate input bandwidth FPGA + GPU architecture for low-latency acquisition, processing, recording, streaming, and Edge AI Optional real-time FPGA image processing, enhancement, and compression IPs The FantoVision20-CL is the ideal choice when you need deterministic Camera Link camera acquisition in a compact, low-latency Jetson platform. Related ProductsView the Full FantoVision System RangeView the PCIe Camera Link Frame Grabber View the Camera Link Simulator - Published: 2025-09-04 - Modified: 2026-08-31 - URL: https://gidel.com/product/coaxpress-simulator/ - Software Types: CamSim-X - Product categories: Development Tools for Imaging & Vision Applications, High-Speed Camera Simulator - CamSim Camera Simulator for CoaXPress The CamSim-X is a high-performance CoaXPress camera simulator that supports up to four CoaXPress-12 output links at up to 12. 5 Gb/s per link and is designed for testing and validating imaging systems and CoaXPress frame grabbers. Fully compliant with CoaXPress (CXP) standards, it functions as a flexible CXP simulator for generating video streams and test patterns. This accelerates development, supports robust validation, and reduces time-to-market. Performance and Simulation Capabilities The CamSim-X supports all CoaXPress pixel formats and delivers extensive capabilities for developers. It transmits BMP and RAW image files as well as grayscale and color test patterns using its built-in generator. Moreover, users can program image timing and data parameters through an intuitive GUI, providing full control over simulation accuracy and flexibility. As a result, engineers gain both precision and efficiency during testing. CoaXPress Image Output The CamSim-X generates programmable CoaXPress image output to emulate the video stream of a physical CXP camera. Users can transmit predefined images, RAW data, or generated test patterns with configurable resolution, pixel format, timing, link speed, and CoaXPress configuration. This enables repeatable testing of CoaXPress frame grabbers, image-processing pipelines, and complete vision systems without requiring the physical target camera. Flexible Development Tools The CamSim-X offers a complete development environment: Application Software: GUI-based control for Windows and Linux for transmitting images, configuring parameters, defining timing, and displaying results. API Methods: A robust set of APIs for Windows and Linux, enabling tailored simulator applications. User-Configurable CC Lines: Programmable Camera Control lines for versatile triggering and synchronization. In addition, these tools ensure seamless integration into diverse workflows and simplify the process of creating custom test setups. Boosting Productivity and Reducing Costs By enabling simulation in a low-cost lab environment, the CamSim-X eliminates reliance on expensive CoaXPress cameras during early-stage development. Furthermore, its data-flow repetition capability ensures reproducible testing, allowing engineers to validate algorithms and quickly identify and resolve rare bugs. Consequently, teams achieve higher productivity, lower costs, and stronger confidence in their imaging systems. Why Choose the CamSim-X? Fully compliant with CoaXPress standards. Flexible test pattern generation with BMP/RAW and color/grayscale options. FPGA-based transmission for accurate, repeatable simulations. GUI and API support for fast customization. Cost-effective solution for developing and validating imaging pipelines. The CamSim-X provides engineers with a reliable, flexible, and cost-effective CoaXPress simulator built to streamline imaging system development. Related Products View the Full Camera Simulators Range View the Full Range of PCIe CoaXPress Frame Grabbers View the FantoVision40-CXP12: Edge AI CoaXPress System - Published: 2025-06-09 - Modified: 2026-06-06 - URL: https://gidel.com/product/fpga-programming-sdk/ - Product categories: FPGA Compute Acceleration Boards, Development Tools for Imaging & Vision Applications FPGA Programming SDK Gidel's FPGA Programming SDK streamlines development by offering both Board Support Packages (BSPs) and Application Support Packages (ASPs). Optimized for Altera FPGA technology, each serves a unique role in simplifying hardware integration and performance optimization. The BSP provides the essential foundation for FPGA engineers. It includes low-level drivers, configuration files, and host interfaces required to bring up the hardware and ensure seamless communication between the FPGA board and the host system. This setup handles board initialization, memory interfaces, PCIe connectivity, and I/O definitions, forming a reliable base for system development. Gidel further enhances this with its Application Support Package (ASP)—a high-level automation layer that goes beyond traditional BSP functionality. The ASP maps FPGA resources to match the specific needs of your application. It automatically detects active IPs within the FPGA, configures the appropriate data flow, and allows multiple processes to run simultaneously without interference through multi-program parallel access. The ASP’s automation eliminates manual resource allocation and reduces the risk of configuration errors, significantly lowering the overall engineering effort. It enables the system to adapt quickly to changes, improves long-term maintainability, and supports faster deployment cycles. A key benefit of Gidel’s approach is FPGA virtualization. This enables multiple programs or developers to work on the same FPGA simultaneously, each accessing only the required resources. This approach enhances modularity and is ideal for demanding environments such as AI pipelines, high-speed vision, and data acquisition. The ASP can also dynamically allocate any unused FPGA resources, boosting flexibility and ensuring maximum hardware utilization. Whether the workload is heavy or spread across several smaller modules, system performance remains optimized. By simplifying integration and maximizing performance, the ASP helps users' lower development costs and reduce time-to-market. Gidel's FPGA Programming SDK is an integral part of Gidel's ProcVision Suite— a comprehensive environment for developing customizable vision & imaging systems. - Published: 2025-03-12 - Modified: 2026-05-25 - URL: https://gidel.com/product/high-dynamic-range-hdr-ip/ - Product categories: Development Tools for Imaging & Vision Applications, FPGA Image Compression IPs, GIL: FPGA Imaging Libraries (IPs), Low Latency Recording & Streaming Solutions, Aerial Mapping ISP: SkyBoost-RT vs. SkyBoost HDR IP Correction: High Performance Single Exposure While traditional HDR relies on multiple exposures — a method often impractical for applications involving motion or high data rates — Gidel’s High Dynamic Range IP overcomes these limitations with an innovative single-exposure algorithm. This FPGA-based solution delivers uncompromised HDR quality and real-time performance. Superior Image Quality with Unlimited Throughput Gidel’s IP provides real-time, high-quality HDR with virtually zero latency. It stands out by analyzing not only the luminance data of each pixel but also the surrounding pixels, dynamically adjusting HDR processing to account for local luminance variations. This environment-sensitive approach enhances subtle details, even in challenging HRS lighting, to deliver data with exceptional fidelity. HDR IP High-Volume Processing Gidel’s proprietary HDR algorithm uses FPGA architecture to process multiple pixels simultaneously. This enables high-speed, efficient performance across an ultra-wide field of view. It is the ideal solution for high-throughput, outdoor HRS pipelines. Integration in ISP Pipeline Gidel’s HDR correction provides powerful CPU offloading, integrating seamlessly into Gidel’s Mini Jetson Frame Grabbers, PCIe Frame Grabbers and FPGA Modules. This technology is essential for high-dynamic-range requirements in high-end Imaging & Vision applications. High-Quality Demosaicing White Balance Dynamic Luminance Balance Compression IPs (. JPEG, Lossless, Quality+) This modular and customizable approach allows for a fully optimized end-to-end solution to meet the specific demands of any imaging application, ensuring maximum performance with minimal host intervention. - Published: 2024-05-28 - Modified: 2026-04-01 - URL: https://gidel.com/product/modular-vision-sdk-for-fpga/ - Product categories: Products, Modular Imaging Solutions, Development Tools for Imaging & Vision Applications, GIL: FPGA Imaging Libraries (IPs) Modular Vision SDK for FPGA Development Gidel’s ProcVision Suite is a Modular Vision SDK for FPGA Development. It provides a unique ecosystem for building high-performance, custom imaging and vision systems. Gidel offers fully customizable image acquisition and processing platforms that combine FPGA acceleration, smart IP cores, and seamless host integration. This flexibility enables developers to quickly build and deploy tailored solutions, offering a real competitive edge in vision development. The ProcVision Suite allows full customization of the acquisition and processing path for imaging and vision applications. Developers can insert proprietary image processing or AI algorithms directly into the FPGA pipeline. These algorithms combine with Gidel’s robust IPs to optimize performance for real-time applications. Additionally, the platform also supports Gidel’s advanced compression technologies, including the proprietary Quality+ enhancement compression, as well as JPEG and Lossless compression options - vital for reducing bandwidth and storage without compromising image fidelity. Gidel provides the CertifEye toolchain to ensure robust development and fast debugging. It enables real-time verification of user algorithms with live or simulated data. Gidel’s InfiniVision provides flexible infrastructure for multi-Camera grabbing and processing. It supports simultaneous acquisition of over 100 cameras or sensors Gidel’s FantoVision series mini edge computer combines Gidel’s grabbing and processing technology with NVIDIA Jetson. Moreover, this powerful integration transforms the ProcVision Suite into a complete solution for AI edge computing applications. As a result, this system delivers an ideal platform for AI, recording, and streaming applications. In summary, ProcVision Suite is more than a standard development kit. It is a Modular Vision SDK for FPGA-based systems. As a result, this suite empowers developers to accelerate innovation in imaging, AI, and high-speed data acquisition. Moreover, it includes powerful tools, reusable IP cores, and seamless integration features for efficient system development. Consequently, these capabilities enable faster development cycles, easier customization, and scalable deployment across various vision & imaging applications. - Published: 2024-05-27 - Modified: 2026-06-12 - URL: https://gidel.com/product/proc1c10n-fpga-accelerator/ - Software Types: FPGA Compute Acceleration - Product categories: FPGA Compute Acceleration Boards Proc1C10N: AI-Optimized FPGA Accelerator with HBM2 Technology The Proc1C10N™ is a compact, ultra-high-performance FPGA accelerator built on Altera Stratix® 10 NX FPGA. Designed for AI-driven, compute-intensive, and high-bandwidth applications, it not only integrates embedded Tensor blocks with HBM2 memory but also delivers 143 INT8 TOPS / FP16 TFLOPS of processing power. As a result, this FPGA accelerator provides exceptional throughput and efficiency for advanced AI workloads. AI Performance and Memory This AI-focused compute accelerator combines 16 × 25 Gb/s full-duplex transceivers with a robust multi-level memory architecture. Additionally, it features embedded MLABs and M20K, tightly coupled HBM2 and eSRAM, and supports up to 128 GB DDR4. Therefore, the Proc1C10N achieves ultra-low latency and high bandwidth, making it ideal for AI acceleration, HPC, networking, and edge-compute environments. Connectivity and Expansion Options The half-length PCIe Gen3 x16 board includes 4 × QSFP28 ports, a Gidel PHS connector for daughterboards, and 19 GPIOs for peripheral control. Furthermore, the PHS enables up to 128 Gb/s Rx/Tx, ensuring seamless integration with 8 × CoaXPress-12 cameras via a Gidel CXP daughterboard. Consequently, the Proc1C10N is well-suited for real-time vision and edge AI applications. Development Tools Supported by Gidel’s advanced development suite, the Proc1C10N FPGA accelerator streamlines integration and shortens development cycles. Moreover, it supports C and HDL-based design, reducing engineering effort, enhancing reliability, and accelerating time-to-market. Why Choose the Proc1C10N FPGA Accelerator? Embedded Tensor blocks for optimized AI performance HBM2 memory for 10X more DRAM and SRAM bandwidth 143 INT8 TOPS / FP16 TFLOPS for high-demand AI workloads Compact PCIe design for versatile system integration For more accelerator card options, visit FPGA Compute Acceleration - Gidel Target applications: Broadcasting, Image-Processing and Video Analytics: grabbing from 100+ high-bandwidth sensors with real-time image processing, compression and AI application, all running on a single FPGA. Security: deep packet inspection, fraud detection, etc. 5G and Radar: high-bandwidth real-time edge computing Natural Language Processing: speech recognition and speech synthesis - Published: 2024-05-27 - Modified: 2026-06-12 - URL: https://gidel.com/product/proc1c10m-accelerator-card/ - Software Types: FPGA Compute Acceleration - Product categories: FPGA Compute Acceleration Boards Proc1C10M - High-Performance FPGA Accelerator Card with HBM2 Technology The Proc1C10M™ is a compact, ultra-high-performance accelerator card built on Altera Stratix 10 MX. Designed for compute-intensive, low-latency, and high-bandwidth applications, it not only delivers massive processing power but also integrates HBM technology with up to 1,600 Gb/s of I/O bandwidth. As a result, this FPGA accelerator ensures unmatched data throughput for today’s most demanding workloads. Unmatched Performance This compute accelerator integrates 16 × 25 Gb/s full-duplex transceivers and a multi-level memory architecture. Additionally, the memory ecosystem includes embedded MLABs and M20K, tightly coupled HBM and eSRAM, and up to 128 GB DDR4. Therefore, the Proc1C10M offers exceptional processing capabilities and consistent low-latency performance for HPC, AI acceleration, storage, networking, and high-end imaging workloads. Connectivity & Scalability The half-length PCIe Gen3 x16 accelerator card includes 4 × QSFP28 ports, a Gidel PHS connector for daughterboards, and 19 GPIOs for peripheral control. Furthermore, the PHS supports up to 128 Gb/s Rx/Tx, enabling seamless integration with 8 × CoaXPress-12 cameras via a Gidel CXP daughterboard. Consequently, the Proc1C10M is ideal for vision-intensive and real-time applications. Development Tools Supported by Gidel’s advanced development suite, the Proc1C10M FPGA accelerator card simplifies complex project deployment. Moreover, it supports development in both C and HDL, reducing integration time, improving reliability, and accelerating time-to-market. Why Choose the Proc1C10M Accelerator Card? HBM technology for 10X more DRAM and eSRAM bandwidth 1,600 Gb/s I/O bandwidth for high-throughput applications Compact PCIe design with flexible I/O Optimized for HPC, acceleration, networking, storage, and imaging workloads For more accelerator card options, visit FPGA Compute Acceleration - Gidel Target applications: Broadcasting, Image-Processing and Video Analytics: grabbing from 100+ high-bandwidth sensors with real-time image processing, compression and AI application, all running on a single FPGA. Security: deep packet inspection, fraud detection, etc. 5G and Radar: high-bandwidth real-time edge computing Natural Language Processing: speech recognition and speech synthesis - Published: 2024-05-13 - Modified: 2026-08-14 - URL: https://gidel.com/product/proc10a-40-gige-card-smart-nic/ - Software Types: Imaging & Vision - Product categories: GigE Vision Frame Grabbers & Image Processing, Frame Grabbers & Image Processing, Modular Imaging Solutions, Development Tools for Imaging & Vision Applications, FPGA Image Compression IPs, GIL: FPGA Imaging Libraries (IPs), Low Latency Recording & Streaming Solutions, Image Acquisition Solutions: ProcFG vs InfiniVision 4 × 10 GigE Frame Grabber Card for GigE Vision Cameras The Proc10A-40GigE is a high-performance 40 GigE Vision frame grabber card designed for real-time image acquisition, preprocessing, and compression from high-speed 10 GigE Vision cameras in demanding multi-camera vision systems. Powered by Altera Arria 10 FPGA technology, it supports up to 4 × 10 GigE cameras with up to 40 Gb/s aggregate input bandwidth. As a result, it delivers zero-frame-loss acquisition, ultra-low latency, and negligible host CPU load for high-speed and mission-critical imaging applications. Quad 10 GigE Vision Acquisition with Real-Time FPGA Image Processing The Proc10A-40GigE is available as a plug-and-play 40 GigE Vision frame grabber or as part of a complete imaging & vision system with real-time FPGA preprocessing, image enhancement, and compression options. The built-in FPGA can process image data during acquisition, before the data reaches the host PC. This helps reduce bandwidth, storage, and host processing load while preserving low-latency performance for high-speed camera streams. Optional FPGA processing includes Compression, HDR correction, Detection, and additional image enhancement modules. Real-Time FPGA Processing Helps Enable: Reduced bandwidth for high-throughput image acquisition Low-latency processing directly in the acquisition flow Extended recording time through real-time compression Lower host processing load by offloading selected tasks to the FPGA Custom image pipelines using Gidel IPs or user FPGA logic For the full list of available image processing and enhancement options, please refer to the Options tab. Flexible Operating Modes The Proc10A-40GigE supports two operating modes selectable via firmware: InfiniVision: Ideal for synchronized multi-camera setups, combining all camera data, including data acquired across multiple cards, into a single buffer with support for dynamic resolutions and formats. ProcFG: Tailored for precision applications, offering fixed frame sizes, pixel formats, and uncompressed ROI grabbing. As a result, the Proc10A-40GigE adapts to diverse workflows, supporting both synchronized multi-camera systems and streamlined single-camera operations. InfiniVision: Multi-Camera Acquisition and Synchronization Built on Gidel’s InfiniVision architecture, the Proc10A-40GigE addresses key multi-camera challenges, including synchronization, bandwidth, connectivity, and scalability. It supports acquisition from up to 4 × 10 GigE Vision cameras directly, while scalable multi-camera configurations enable synchronized acquisition from 100+ cameras. A PCIe Gen3 x8 host interface provides CPU-free, ultra-fast data transfer, while on-board buffers of up to 33 GB support stable acquisition and real-time FPGA image processing. As a result, the Proc10A-40GigE delivers reliable performance in high-speed, high-resolution imaging systems. SDK and Development Tools The Proc10A-40GigE is supported by Gidel’s SDK, featuring intuitive GUIs and APIs for streamlined integration. Additionally, the ProcVision Suite adds advanced FPGA programming, debugging, and validation tools, enabling developers to customize data flows, real-time processing, and compression pipelines with ease. Consequently, they can create optimized, application-specific solutions faster and with reduced risk. Why Choose the Proc10A-40GigE Frame Grabber? Quad 10 GigE Vision FPGA frame grabber for high-speed multi-camera image acquisition Up to 40 Gb/s aggregate input bandwidth FPGA architecture for low-latency acquisition, processing, recording, and streaming Scalable InfiniVision architecture for synchronized multi-camera systems Advanced SDK and ProcVision Suite for rapid development and integration Optional real-time FPGA processing, image enhancement, and compression IPs The Proc10A-40GigE is the ideal choice when your workload requires multi-camera 10 GigE Vision acquisition, low-latency FPGA processing, and reliable image transfer to a host PC. Related Products View the Full Range of PCIe GigE Vision Frame Grabbers View the FantoVision20-GigE: Edge AI GigE Vision System - Published: 2023-08-16 - Modified: 2026-06-16 - URL: https://gidel.com/product/improved-snr-real-time-lossless-compression/ - Product categories: Modular Imaging Solutions, FPGA Image Compression IPs, GIL: FPGA Imaging Libraries (IPs), Low Latency Recording & Streaming Solutions FPGA Image Compression for High-Bandwidth Imaging Gidel’s Quality+ is a proprietary FPGA image compression IP developed as a high-performance alternative to traditional lossless compression. Quality+ performs real-time FPGA-based compression for Color Filter Array formats, such as Bayer, as well as monochrome and RGB images and videos. Designed for high-speed, high-bandwidth imaging, Quality+ achieves compression ratios up to 10:1+ while preserving the original image quality. Unlike conventional visually lossless methods that compromise fidelity, Quality+ maintains the original signal-to-noise ratio, SNR, by replacing unnecessary noise with compression-efficient data. This maximizes bandwidth efficiency without degrading image quality. Adaptive FPGA Compression with On-the-Fly Training With on-the-fly adaptive training, Quality+ continuously optimizes compression for each video stream in real time. Operating entirely on the FPGA, it removes CPU and GPU load while supporting throughput exceeding 1. 2 GPixels/s with less than one frame period of latency. Ideal for high-bandwidth Imaging & Vision Systems, including medical imaging, surveillance, and defense applications, Quality+ reduces data rates and storage requirements while preserving image integrity in real time. Related Products View Gidel's Lossless Compression View Gidel’s JPEG Compression - Published: 2023-07-10 - Modified: 2026-08-14 - URL: https://gidel.com/product/hawkeye-20gige-vision-frame-grabber/ - Software Types: Imaging & Vision - Product categories: GigE Vision Frame Grabbers & Image Processing, Frame Grabbers & Image Processing, Modular Imaging Solutions, Development Tools for Imaging & Vision Applications, FPGA Image Compression IPs, GIL: FPGA Imaging Libraries (IPs), Low Latency Recording & Streaming Solutions, Image Acquisition Solutions: ProcFG vs InfiniVision 2-Port 10 GigE Frame Grabber for GigE Vision Cameras The HawkEye-20GigE is a high-performance 20 GigE Vision frame grabber designed for real-time image acquisition, preprocessing, and compression from high-speed 10 GigE Vision cameras in demanding multi-camera vision systems. Powered by Altera Arria 10 FPGA technology, it supports up to 2 × 10 GigE cameras with up to 20 Gb/s aggregate input bandwidth. As a result, it delivers zero-frame-loss acquisition, ultra-low latency, and negligible host CPU load for high-speed and mission-critical imaging applications. Dual 10 GigE Vision Acquisition with Real-Time FPGA Image Processing The HawkEye-20GigE is available as a plug-and-play 10 GigE Vision frame grabber or as part of a complete imaging & vision system with real-time FPGA preprocessing, image enhancement, and compression options. The built-in FPGA can process image data during acquisition, before the data reaches the host PC. This helps reduce bandwidth, storage, and host processing load while preserving low-latency performance for high-speed camera streams. Optional FPGA processing includes Compression, HDR correction, Detection, and additional image enhancement modules. Real-Time FPGA Processing Helps Enable: Reduced bandwidth for high-throughput image acquisition Low-latency processing directly in the acquisition flow Extended recording time through real-time compression Lower host processing load by offloading selected tasks to the FPGA Custom image pipelines using Gidel IPs or user FPGA logic For the full list of available image processing and enhancement options, please refer to the Options tab. Flexible Operating Modes The HawkEye-20GigE supports two operating modes selectable via firmware: InfiniVision: Ideal for synchronized multi-camera setups, combining all camera data, including data acquired across multiple cards, into a single buffer with support for dynamic resolutions and formats. ProcFG: Tailored for precision applications, offering fixed frame sizes, pixel formats, and uncompressed ROI grabbing. As a result, the HawkEye-20GigE adapts to diverse workflows, supporting both synchronized multi-camera systems and streamlined single-camera operations. InfiniVision: Multi-Camera Acquisition and Synchronization Built on Gidel’s InfiniVision architecture, the HawkEye-20GigE addresses key multi-camera challenges, including synchronization, bandwidth, connectivity, and scalability. It supports acquisition from up to 2 × 10 GigE Vision cameras directly, while scalable multi-camera configurations enable synchronized acquisition from 100+ cameras. A PCIe Gen3 x8 host interface provides CPU-free, ultra-fast data transfer, while on-board buffers of up to 17 GB support stable acquisition and real-time FPGA image processing. As a result, the HawkEye-20GigE delivers reliable performance in high-speed, high-resolution imaging systems. SDK and Development Tools The HawkEye-20GigE is supported by Gidel’s SDK, offering intuitive GUIs and APIs for streamlined system integration. Additionally, the ProcVision Suite provides advanced FPGA programming, debugging, and validation tools. Consequently, developers can rapidly customize data flows, implement real-time processing, and optimize compression pipelines, reducing development time and risk. Why Choose the HawkEye-20GigE Frame Grabber? Dual 10 GigE Vision FPGA frame grabber for high-speed multi-camera image acquisition Up to 20 Gb/s aggregate input bandwidth FPGA architecture for low-latency acquisition, processing, recording, and streaming Scalable InfiniVision architecture for synchronized multi-camera systems Advanced SDK and ProcVision Suite for rapid development and integration Optional real-time FPGA processing, image enhancement, and compression IPs The HawkEye-20GigE is the ideal choice when your workload requires high-speed GigE Vision acquisition, low-latency FPGA processing, and reliable image transfer to a host PC. Related Products View the Full Range of PCIe GigE Vision Frame Grabbers View the FantoVision20-GigE: Edge AI GigE Vision System - Published: 2023-06-29 - Modified: 2026-06-16 - URL: https://gidel.com/product/jpeg-encoder/ - Product categories: FantoVision20 Edge AI with FPGA Frame Grabbers, GigE Vision Frame Grabbers & Image Processing, CoaXPress Frame Grabbers & Image Processing, Frame Grabbers & Image Processing, Camera Link Frame Grabbers & Image Processing, Mini FPGA Modules, Modular Imaging Solutions, FPGA Image Compression IPs, GIL: FPGA Imaging Libraries (IPs), Low Latency Recording & Streaming Solutions, Aerial Mapping ISP: SkyBoost-RT vs. SkyBoost JPEG Encoder on FPGA for High-Speed Imaging Gidel’s JPEG encoder performs real-time image compression directly on the FPGA, enabling high-speed camera acquisition with low latency, reduced bandwidth, and minimal host CPU load. Designed for Imaging & Vision systems, the JPEG encoder IP supports YCbCr input with optional conversion from RGB, Bayer, or monochrome formats. Compression quality is selectable, allowing users to balance image quality, bandwidth, and storage requirements for JPEG or JPG image output according to the application. The encoder is optimized for compact FPGA implementation, making it suitable for small FPGA devices, FPGA-based frame grabbers, and multiple parallel encoder instances on larger FPGA platforms. It includes a host interface and API suite for software integration. Example performance includes 4:2:2 encoding at 540 MPixels/s and up to 1. 84 GPixels/s, with latency as low as 130 μs. Standard operation supports 8 bits per component, with higher bit-depth options available on request. FPGA Integration Across Gidel Imaging Platforms Gidel integrates the JPEG encoder across its FPGA-based Imaging & Vision platforms. These include FantoVision Mini Edge AI Systems, High-Bandwidth PCIe Frame Grabbers, FPGA Compute Accelerators, and Ultra-Compact FPGA Modules. The FPGA compresses image data before sending it to the host system. As a result, the encoder reduces bandwidth, storage requirements, and CPU load. It also preserves host resources for downstream processing, analysis, and AI applications. Related Products View Gidel's Lossless Compression View Gidel's Quality+ Compression - Published: 2023-06-29 - Modified: 2026-06-16 - URL: https://gidel.com/product/fpga-lossless-image-compression/ - Software Types: Compression IP's - Product categories: FantoVision20 Edge AI with FPGA Frame Grabbers, GigE Vision Frame Grabbers & Image Processing, CoaXPress Frame Grabbers & Image Processing, Camera Link Frame Grabbers & Image Processing, Mini FPGA Modules, Modular Imaging Solutions, FPGA Image Compression IPs, GIL: FPGA Imaging Libraries (IPs), Low Latency Recording & Streaming Solutions, Aerial Mapping ISP: SkyBoost-RT vs. SkyBoost Lossless Image Compression on FPGA for High-Speed Imaging Gidel’s Lossless Image Compression IP targets FPGA-based Imaging & Vision applications. This lossless image compression IP performs real-time compression for Color Filter Array, CFA, such as Bayer, monochrome, and RGB images and videos. It supports multi-camera and multi-sensor systems at pixel clock rates exceeding 1 Gpixel/s, using minimal FPGA resources and power. In real-world video tests, it achieves a 1:2. 3 compression ratio at 8 bits per pixel. Higher bit configurations are available upon request. The IP integrates with Gidel’s FPGA ecosystem, enabling tailored solutions with image processing, vision algorithms, and concurrent recording. Frame and Video Compression Modes Two compression modes are available: Frame compression – compress individual images. Video compression – compress video using I and P frames. Compression can be optimized via pre-training on sample image data or on-the-fly training from real-time data. Related Products View Gidel's JPEG Compression View Gidel's Quality+ Compression - Published: 2023-03-25 - Modified: 2026-08-31 - URL: https://gidel.com/product/camera-link-simulator/ - Software Types: CamSim-CL - Product categories: Development Tools for Imaging & Vision Applications, High-Speed Camera Simulator - CamSim Camera Simulator for Camera Link The CamSim-CL is a high-performance Camera Link simulator that supports Base, Medium, Full, Deca, and Dual Base configurations and is designed for testing and validating imaging systems and Camera Link frame grabbers. Fully compliant with the Camera Link v2. 0 standard, it functions as a flexible CameraLink simulator for generating video streams and test patterns. This accelerates development, supports robust system validation, and reduces time-to-market. Performance and Simulation Capabilities The CamSim-CL supports all Camera Link v2. 0 configurations and delivers unmatched flexibility for developers. It transmits BMP and RAW image files as well as grayscale and color test patterns using its built-in generator. Moreover, users can program image timing and data parameters through an intuitive GUI, providing full control over simulation accuracy and flexibility. As a result, developers gain both precision and efficiency during testing. Camera Link Image Output The CamSim-CL generates programmable Camera Link image output to emulate the video stream of a physical Camera Link camera. Users can transmit predefined images, RAW data, or generated test patterns with configurable resolution, pixel format, timing, and Camera Link configuration. This enables repeatable testing of Camera Link frame grabbers, image-processing pipelines, and complete vision systems without requiring the physical target camera. Flexible Development Tools The CamSim-CL offers a complete development environment: Application Software: GUI-based control for Windows and Linux for transmitting images, configuring parameters, defining timing, and displaying results. API Methods: A robust set of APIs for Windows and Linux, enabling tailored simulator applications. User-Configurable CC Lines: Programmable Camera Control lines for versatile triggering and synchronization. In addition, these tools ensure seamless integration into diverse workflows and simplify the process of creating custom test setups. Boosting Productivity and Reducing Costs By enabling simulation in a low-cost lab environment, the CamSim-CL eliminates reliance on expensive Camera Link cameras during early-stage development. In addition, its data-flow repetition capability ensures reproducible testing, allowing engineers to validate algorithms and quickly identify and resolve rare bugs. Consequently, teams gain higher productivity and stronger confidence in their imaging systems. Why Choose the CamSim-CL? Fully compliant with Camera Link v2. 0. Flexible test pattern generation with BMP/RAW and color/grayscale options. FPGA-based transmission for accurate, repeatable simulations. GUI and API support for fast customization. Cost-effective solution for developing and validating imaging pipelines. The CamSim-CL provides engineers with a reliable, flexible, and cost-effective Camera Link simulator built to streamline imaging system development. Related Products View the Full Camera Simulators Range View the PCIe Camera Link Frame Grabber View the FantoVision20-CL: Edge AI Camera Link System - Published: 2023-03-24 - Modified: 2026-07-05 - URL: https://gidel.com/product/tiny-fpga-modules/ - Software Types: Imaging & Vision - Product categories: Mini FPGA Modules, Modular Imaging Solutions, Development Tools for Imaging & Vision Applications, FPGA Image Compression IPs, GIL: FPGA Imaging Libraries (IPs), Low Latency Recording & Streaming Solutions, Image Acquisition Solutions: ProcFG vs InfiniVision, Aerial Mapping ISP: SkyBoost-RT vs. SkyBoost FDB Series: Tiny FPGA Modules for High-Performance Embedded Systems The FDB series includes FDB16 (49 × 54 mm), FDB27 (58 × 58 mm), and FDB66 (58 × 58 mm). These modules rank among the tiniest FPGA modules available on the market today, making them ideal for custom PCIe-based or standalone, space-constrained systems. Moreover, their ultra-compact form factor enables seamless integration into embedded designs while maintaining full performance capability. Performance and Memory in the FDB Tiny FPGA Modules Each FDB module uses an Altera Arria 10 GX FPGA, supports up to 10 GB DRAM at 24 GB/s, and includes 16 × 14. 2 Gb/s transceivers (10 full duplex plus 2 RX only). Consequently, this tiny FPGA platform delivers high performance at a competitive price. In addition, the robust design supports mission-critical tasks and long-term deployment. Therefore, the platform suits applications that require efficiency, durability, and scalability. Tiny Processing Modules with Real-Time FPGA Image Processing Gidel’s FDB ultra-compact FPGA modules are available as compact FPGA platforms for embedded imaging systems or as part of a complete Imaging & Vision solution with real-time FPGA preprocessing, image enhancement, and compression options. The built-in FPGA can process image data directly at the edge, close to the camera interface and before the data reaches the host system. This helps reduce bandwidth, storage, and host processing load while preserving low-latency performance for compact high-speed imaging applications. Optional FPGA processing includes Compression, HDR correction, Detection, and additional image enhancement modules. Real-Time FPGA Processing Helps Enable: Reduced bandwidth for high-throughput image acquisition Low-latency processing directly in the acquisition flow Extended recording time through real-time compression Lower host processing load by offloading selected tasks to the FPGA Custom image pipelines using Gidel IPs or user FPGA logic For the full list of available image processing and enhancement options, please refer to the Options tab. Integrated Vision Architecture for Embedded FPGA Processing Gidel’s vision architecture, implemented within the FDB tiny FPGA modules, supports both the InfiniVision multi-camera vision system and the ProcFG deterministic image acquisition system. Together, they address critical embedded vision challenges, including bandwidth handling, synchronization, connectivity, and system scalability. InfiniVision enables flexible, synchronized multi-camera acquisition across large sensor arrays, while ProcFG provides a deterministic acquisition model optimized for fixed timing, guaranteed frame capture, and line-scan–oriented pipelines. This architectural flexibility allows the FDB platform to manage multiple high-speed data sources, merge parallel sensor inputs, and maintain predictable real-time behavior. On-module FPGA memory, advanced buffering, and deterministic dataflow control ensure stable acquisition and enable real-time image processing. As a result, FDB modules deliver reliable and predictable performance, even in compact, space-constrained, high-resolution embedded systems. Flexible Integration Options The FDB modules adapt to diverse integration needs. They can operate as standalone embedded processing engines inside miniature systems or as part of a fully customized solution incorporating on-board FPGA image enhancement, real-time compression, precise multi-sensor synchronization, and advanced I/O control. As a result, the FDB series provides exceptional flexibility and scalability for any embedded imaging or vision architecture. SDK, Development Tools, and Integration The FDB modules are supported by Gidel’s SDK with intuitive GUIs and APIs for fast system integration. The ProcVision Suite provides advanced FPGA programming, debugging, and validation tools, enabling rapid customization of data flows and real-time processing pipelines. In addition, the FDB series features an advanced multi-port DRAM controller that splits memory into up to 16 parallel logical banks with simultaneous access. Each module is supplied with a PCIe carrier board and development utilities, allowing engineers to begin testing immediately. As a result, development cycles are shorter, reliability is higher, and time-to-market is significantly improved. Why Choose the FDB modules? Tiny footprints: FDB16 49 × 54 mm, FDB27/FDB66 58 × 58 mm Lightweight design: FDB16 30 g, FDB27/FDB66 35 g Altera Arria 10 FPGA architecture with up to 10 GB DRAM at 24 GB/s Advanced SDK and ProcVision Suite for rapid development and integration Optional real-time FPGA processing, image enhancement, and compression IPs The FDB modules are the ideal choice when your workload requires compact FPGA processing, low-latency imaging pipelines, and flexible integration into embedded or space-limited systems. Related Products View the Full FPGA Modules Range - Published: 2023-03-23 - Modified: 2026-07-05 - URL: https://gidel.com/product/small-fpga-module/ - Software Types: Imaging & Vision - Product categories: Mini FPGA Modules, Modular Imaging Solutions, Development Tools for Imaging & Vision Applications, FPGA Image Compression IPs, GIL: FPGA Imaging Libraries (IPs), Low Latency Recording & Streaming Solutions, Aerial Mapping ISP: SkyBoost-RT vs. SkyBoost Proc10M: Small FPGA Module for High-Performance Embedded Systems The Proc10M™ is a compact, high-performance FPGA module designed for embedded and edge computing applications. Powered by the Altera Stratix® 10 MX FPGA, it delivers up to 10× higher memory bandwidth than traditional DDR4/QDR systems. Moreover, it integrates 300 GB/s DRAM throughput, up to 128 GB DDR4 on the carrier, and 1,600 Gb/s I/O bandwidth, ensuring seamless integration into high-bandwidth embedded designs while providing exceptional processing capability. Performance and Memory in the Proc10M Module Supporting transceiver speeds up to 26 Gb/s and up to 374 FPGA I/Os, the Proc10M offers extreme I/O flexibility for high-speed embedded systems. Consequently, it delivers outstanding data throughput in a compact footprint of 97. 4 × 101 mm. Additionally, its robust hardware architecture ensures reliable operation in demanding environments and provides a cost-efficient solution for long-term deployment. Therefore, it is well-suited for applications requiring high bandwidth, real-time processing, and scalable embedded compute. Small Processing Module with Real-Time FPGA Image Processing The Proc10M is available as a high-performance FPGA module for embedded imaging systems or as part of a complete Imaging & Vision solution with real-time FPGA preprocessing, image enhancement, and compression options. The built-in FPGA can process image data directly at the edge, close to the camera interface and before the data reaches the host system. This helps reduce bandwidth, storage, and host processing load while preserving low-latency performance for compact high-speed imaging applications. Optional FPGA processing includes Compression, HDR correction, Detection, and additional image enhancement modules. Real-Time FPGA Processing Helps Enable: Reduced bandwidth for high-throughput image acquisition Low-latency processing directly in the acquisition flow Extended recording time through real-time compression Lower host processing load by offloading selected tasks to the FPGA Custom image pipelines using Gidel IPs or user FPGA logic For the full list of available image processing and enhancement options, please refer to the Options tab. Integrated Vision Architecture for Embedded FPGA Processing Gidel’s vision architecture, implemented on the Proc10M FPGA modules, supports both the InfiniVision multi-camera vision system and the ProcFG deterministic image acquisition system. Together, they address high-bandwidth acquisition, synchronization, buffering, and scalable processing requirements in demanding vision platforms. InfiniVision enables flexible, synchronized acquisition across large camera arrays and multi-stream configurations, while ProcFG provides a deterministic acquisition model optimized for fixed timing, guaranteed frame capture, and line-scan–oriented pipelines. This dual approach allows Proc10M module to handle multiple high-speed data sources, merge parallel sensor inputs, and maintain predictable real-time behavior under sustained load. With high-performance FPGA resources, on-board memory, and deterministic dataflow control, the Proc10M module support stable acquisition and real-time image processing at scale. As a result, they deliver reliable and predictable performance in high-throughput, high-resolution vision systems where bandwidth density and timing control are critical. Flexible Integration Options The Proc10M integrates easily into diverse system architectures. It can serve as a standalone processing engine or as part of a customized solution featuring FPGA-based enhancement, real-time compression, synchronized acquisition, and advanced I/O control. As a result, the Proc10M provides exceptional flexibility and scalability for embedded vision, sensing, and high-bandwidth applications. SDK, Development Tools, and Integration The Proc10M is supported by Gidel’s SDK and ProcVision Suite, providing intuitive GUIs, APIs, debugging, programming, and validation tools. Consequently, developers can rapidly design custom pipelines, optimize FPGA resources, and accelerate integration with reduced engineering risk. The Proc10M also benefits from Gidel’s advanced DRAM/memory architecture and is fully compatible with Gidel or customer-designed carrier boards, enabling immediate system start-up and rapid prototyping. As a result, teams can shorten development cycles, improve reliability, and accelerate time-to-market for high-bandwidth embedded applications. Why Choose the Proc10M? Compact footprint: 97. 4 × 101 mm Altera Stratix 10 MX FPGA architecture with HBM and up to 128 GB DDR4 Up to 300 GB/s DRAM throughput and up to 1,600 Gb/s I/O bandwidth Advanced SDK and ProcVision Suite for rapid development and integration Optional real-time FPGA processing, image enhancement, and compression IPs The Proc10M is the ideal choice when your workload requires high-bandwidth FPGA processing, large memory capacity, and compact integration into demanding embedded systems. Related Products View the Full FPGA Modules Range - Published: 2023-03-23 - Modified: 2026-07-05 - URL: https://gidel.com/product/fpga-for-ai/ - Software Types: Imaging & Vision - Product categories: FPGA Compute Acceleration Boards, Mini FPGA Modules, Modular Imaging Solutions, Development Tools for Imaging & Vision Applications, FPGA Image Compression IPs, GIL: FPGA Imaging Libraries (IPs), Low Latency Recording & Streaming Solutions, Aerial Mapping ISP: SkyBoost-RT vs. SkyBoost Proc10N: Compact FPGA for AI and High-Performance Embedded Systems The Proc10N™ is a compact FPGA for AI module powered by the Altera Stratix® 10 NX FPGA. It delivers exceptional performance for AI acceleration, compute-intensive processing, and low-latency edge systems. With integrated Tensor Blocks, HBM2 memory, and high-bandwidth data interfaces, the Proc10N offers unparalleled throughput for high-speed embedded designs. Moreover, its compact form factor ensures seamless integration into advanced embedded platforms while maintaining maximum compute capability. Performance and Memory in the Proc10N Module Each Proc10N module integrates HBM2 memory, providing 10× higher DRAM/SRAM bandwidth compared to discrete DDR4 and QDR technologies. It also delivers 143 INT8 TOPS / FP16 TFLOPS through dedicated Tensor Blocks and offers 1,600 Gb/s of customizable I/O for extreme data throughput. Consequently, the Proc10N delivers industry-leading compute density at a competitive SWaP profile. Additionally, its robust hardware architecture ensures reliable operation in demanding, mission-critical environments and provides a long-term, cost-efficient solution for complex embedded systems. Therefore, it is ideal for applications requiring deep learning, real-time inference, high-bandwidth acquisition, and deterministic system behavior. AI-Focused Processing Module with Real-Time FPGA Image Processing The Proc10N is available as a high-performance FPGA module for AI, high-bandwidth compute, and embedded imaging systems, or as part of a complete Imaging & Vision solution with real-time FPGA preprocessing, image enhancement, and compression options. The built-in FPGA can process image data directly at the edge, close to the camera interface and before the data reaches the host system. This helps reduce bandwidth, storage, and host processing load while preserving low-latency performance for compact high-speed imaging applications. Optional FPGA processing includes Compression, HDR correction, Detection, and additional image enhancement modules. Real-Time FPGA Processing Helps Enable: Reduced bandwidth for high-throughput image acquisition Low-latency processing directly in the acquisition flow Extended recording time through real-time compression Lower host processing load by offloading selected tasks to the FPGA Custom image pipelines using Gidel IPs or user FPGA logic For the full list of available image processing and enhancement options, please refer to the Options tab. Integrated Vision Architecture for Embedded FPGA Processing Gidel’s vision architecture, implemented on the Proc10N FPGA modules, supports both the InfiniVision multi-camera vision system and the ProcFG deterministic image acquisition system. Together, they address high-bandwidth acquisition, synchronization, buffering, and scalable processing requirements in demanding vision platforms. InfiniVision enables flexible, synchronized acquisition across large camera arrays and multi-stream configurations, while ProcFG provides a deterministic acquisition model optimized for fixed timing, guaranteed frame capture, and line-scan–oriented pipelines. This dual approach allows Proc10N module to handle multiple high-speed data sources, merge parallel sensor inputs, and maintain predictable real-time behavior under sustained load. With high-performance FPGA resources, on-board memory, and deterministic dataflow control, the Proc10N module support stable acquisition and real-time image processing at scale. As a result, they deliver reliable and predictable performance in high-throughput, high-resolution vision systems where bandwidth density and timing control are critical. Flexible Integration Options The Proc10N adapts to diverse integration needs. It can operate as a standalone AI/processing engine or as part of a fully customized solution including FPGA-based image enhancement, real-time compression, multi-sensor aggregation, and advanced I/O control. As a result, the Proc10N provides exceptional flexibility and scalability for high-bandwidth vision, AI, and sensing architectures. SDK, Development Tools, and Integration The Proc10N is supported by Gidel’s SDK, providing intuitive GUIs and APIs for streamlined system integration. Additionally, the ProcVision Suite offers advanced FPGA programming, debugging, and validation tools. Consequently, developers can rapidly build custom dataflows, AI pipelines, and high-bandwidth processing systems while reducing development time and integration risk. The module also benefits from Gidel’s advanced multi-port memory architecture, enabling efficient access to HBM2 resources and supporting hundreds of simultaneous operations. Furthermore, each module is supported by Gidel or customer-designed carrier boards, enabling immediate system bring-up and rapid prototyping. As a result, development cycles are shortened, reliability is improved, and time-to-market is accelerated — making the Proc10N ideal for fast-paced, mission-critical industries. Why Choose the Proc10N? AI-focused FPGA module for high-performance embedded and edge systems Compact footprint: 97. 4 × 101 mm HBM2 memory for high-bandwidth data movement and AI acceleration Advanced SDK and ProcVision Suite for rapid development and integration Optional real-time FPGA processing, image enhancement, and compression IPs The Proc10N is the ideal choice when your workload requires FPGA-based AI acceleration, high-throughput data handling, and compact integration into advanced embedded or edge systems. Related Products View the Full FPGA Modules Range - Published: 2023-03-23 - Modified: 2026-06-12 - URL: https://gidel.com/product/low-power-accelerator-board/ - Software Types: FPGA Compute Acceleration - Product categories: FPGA Compute Acceleration Boards HawkEye: Low Power Accelerator Board The HawkEye™ is a low-profile, low power accelerator board built on Altera Arria 10 GX FPGA technology. Designed for compact, power-sensitive environments, it combines robust computational performance with exceptional energy efficiency. The HawkEye delivers up to 480K logic elements (LEs), IEEE-compliant floating-point capability, and peak data transfer rates of 28 Gb/s through 2 × SFP+ links. With its PCIe Gen3 x8 host interface and on-board memory up to 18 GB DDR4, the HawkEye provides a powerful yet efficient solution for modern embedded and industrial computing applications. Performance and Memory The HawkEye integrates 1–2 GB DDR4, embedded SRAM, and up to 16 GB DDR4 SoDIMM (for larger FPGA devices), supporting 48 parallel memory ports for maximum bandwidth utilization. As a result, it offers high-throughput data handling and low-latency operation while maintaining exceptional power efficiency, starting at less than 12 W. Connectivity and Expansion Options The HawkEye features 2 SFP+ links providing up to 28 Gb/s, alongside a variety of I/O options including RS422, Opto-coupler, external clock, LVDS, LVTTL (3V), and 30V/0. 9A output. Furthermore, the platform can operate either as a PCIe-based compute accelerator or in stand-alone mode, delivering flexibility for diverse deployment scenarios. Consequently, it is ideal for applications demanding reliability and low power in a compact footprint. Optional SoC Capability The HawkEye family also includes an SoC variant with a dual-core ARM processor based on Arria® 10 GX devices. In addition, a MicroSD slot supports large program images for fully stand-alone operation, enhancing versatility in embedded use cases. Development Tools and Reliability Supported by Gidel’s advanced development suite, the HawkEye low power accelerator board simplifies system integration and accelerates deployment. Moreover, the platform has been engineered for high reliability with an MTBF exceeding 1 million hours, ensuring long-term dependability in mission-critical environments. Why Choose the HawkEye Accelerator Board? Altera Arria® 10 FPGA with up to 480K logic elements Under 12 W power consumption for energy-efficient performance Up to 18 GB DDR4 memory with 48 parallel ports 28 Gb/s connectivity via dual SFP+ and PCIe Gen3 x8 SoC variant with dual-core ARM processor and stand-alone operation High reliability with MTBF beyond 1 million hours For more accelerator card options, visit FPGA Compute Acceleration - Gidel Application examples: Network Security, Processing and Analysis DSP and High-Performance Reconfigurable Computing (HPRC) Computational Finance and High Frequency Trading (HFT) Deep Packet Inspection Life Science Applications Data Analytics Surveillance, Machine Vision, and Imaging - Published: 2023-03-22 - Modified: 2026-06-12 - URL: https://gidel.com/product/proc10s-accelerator-board/ - Software Types: FPGA Compute Acceleration - Product categories: FPGA Compute Acceleration Boards Proc10S: Accelerator Board The Proc10S™ is a high-performance, scalable accelerator board built on Altera Stratix® 10 GX FPGA technology. Designed for compute-intensive, high-bandwidth, and low-latency workloads, it not only delivers peak single-precision performance of up to 10 TFLOPS but also ensures the flexibility needed for next-generation Data Centers applications. With 2. 8 million logic elements, 260 GB DDR4 memory, and an optional Quad-core 64-bit ARM Cortex-A53 processor, the Proc10S provides the processing power and adaptability required for evolving infrastructures. Performance and Memory This powerful accelerator integrates a 16-lane PCIe Gen3 interface with 25/14. 1 Gb/s SERDES transceivers for ultra-fast connectivity. Additionally, it supports up to 400 Gb/s throughput via 4 × QSFP28 or a combination of 2 × QSFP28, 2 × SFP28, and Gidel’s proprietary high-speed PHS connector. As a result, the Proc10S delivers unmatched bandwidth and responsiveness for HPC, storage, networking, and real-time data-processing environments. Connectivity and Expansion Options The Proc10S offers abundant I/O and expansion capabilities, ensuring seamless integration into diverse Data Centers infrastructures. Furthermore, its flexible architecture supports a wide range of applications, including broadcasting, video analytics, 5G infrastructure, and security tasks such as deep packet inspection and fraud detection. Consequently, it provides the scalability and versatility required to address the most demanding workloads. Development Tools Supported by Gidel’s advanced development suite, the Proc10S accelerator board streamlines integration and simplifies development. Moreover, it supports C and HDL-based workflows, reducing engineering effort, enhancing reliability, and shortening time-to-market for mission-critical solutions. In addition, its robust toolchain allows developers to maximize FPGA resources efficiently, ensuring long-term value in high-performance environments. Why Choose the Proc10S Accelerator Board? Altera Stratix® 10 FPGA with up to 2. 8 million logic elements. 260 GB DDR4 memory with optional ARM Cortex-A53 SoC. Up to 10 TFLOPS single-precision performance. 400 Gb/s total I/O bandwidth with PCIe Gen3 × 16 and QSFP28 ports. Ideal for Data Centers, HPC, 5G, security, and AI workloads. For more accelerator board options, refer to FPGA Compute Acceleration - Gidel Application examples: Digital Signal Processing (DSP) and High-Performance Reconfigurable Computing (HPRC) High Speed, Low-latency Networking and Network Analysis Life Science Applications Data Centers Linear Algebra and 3D Applications Computational Finance and HFT Data Analytics Deep Packet Inspection Surveillance, Machine Vision, and Imaging High Performance Acquisition Systems - Published: 2023-03-22 - Modified: 2026-05-21 - URL: https://gidel.com/product/multi-camera-vision-system/ - Product categories: Products, Modular Imaging Solutions, Development Tools for Imaging & Vision Applications, FPGA Image Compression IPs, GIL: FPGA Imaging Libraries (IPs), Low Latency Recording & Streaming Solutions, Image Acquisition Solutions: ProcFG vs InfiniVision InfiniVision: Scalable Multi-Camera Acquisition System InfiniVision is a high-performance multi-camera system that powers Gidel’s scalable image acquisition platform, enabling synchronized capture, processing, and recording across 100+ sensors for applications that demand massive throughput and coordinated operation at scale. Scalable Architecture for Server and Edge InfiniVision is designed for both centralized server-based architectures and compact embedded deployments: Hardware Support: Deploy on Gidel PCIe Frame Grabbers, Mini Jetson Frame Grabber Systems, or PGA Modules. Control: Includes a ready-to-use GUI and a comprehensive API for full control over the FPGA-based acquisition and recording pipeline. Interfaces: Supports GigE Vision, CoaXPress, and Camera Link, with custom protocol support available upon request. Synchronized Image Acquisition and Recording As a multi-camera vision acquisition system, InfiniVision coordinates acquisition across large camera arrays. It keeps image data from all cameras aligned in time. This capability is critical for systems that rely on spatial or temporal correlation between multiple viewpoints. The platform handles very high aggregate throughput and high-speed recording. Some configurations can exceed 100,000 FPS for uncompressed image streams, depending on the hardware setup. FPGA resources distribute acquisition and preprocessing tasks, which helps maintain stable operation under sustained load as camera counts and data rates grow. Flexible Frame Handling and Inline Image Processing InfiniVision captures image data on the fly and does not enforce static frame definitions. Each camera, and even each frame, can use different resolutions, pixel formats, or dynamic ROIs. This approach allows designers to combine heterogeneous camera types and adapt acquisition behavior in real time. It also avoids reconfiguration or downtime. The acquisition path includes modular inline processing blocks such as Image Signal Processing (ISP) and image compression. These FPGA-based blocks help balance image quality, bandwidth, storage, and latency. They do so while preserving synchronized multi-camera operation. For applications that require strict determinism, guaranteed frame capture, or line-scan–oriented acquisition, Gidel also offers ProcFG. While InfiniVision focuses on flexible, large-scale, synchronized multi-camera systems, ProcFG is optimized for deterministic image acquisition pipelines where fixed timing, controlled buffering, and complete frame integrity take priority. Why Choose the InfiniVision? InfiniVision targets vision systems that must scale to large camera counts. It maintains synchronized acquisition and reliable high-speed recording as systems grow. OEMs and system integrators can capture, process, and record large volumes of image data without rigid frame definitions or camera limitations. By combining flexible multi-camera acquisition, inline FPGA processing, and scalable recording in one architecture, InfiniVision reduces system complexity. It also lowers long-term integration risk. This approach lets Imaging & Vision designs evolve from early prototypes to fleet deployments while preserving software investment, acquisition behavior, and performance consistency. - Published: 2023-03-22 - Modified: 2026-08-14 - URL: https://gidel.com/product/proc1c10m-100gige-frame-grabber/ - Software Types: Imaging & Vision - Product categories: GigE Vision Frame Grabbers & Image Processing, Frame Grabbers & Image Processing, Modular Imaging Solutions, Development Tools for Imaging & Vision Applications, FPGA Image Compression IPs, GIL: FPGA Imaging Libraries (IPs), Low Latency Recording & Streaming Solutions, Image Acquisition Solutions: ProcFG vs InfiniVision 12 × 10 GigE Frame Grabber for GigE Vision Cameras The Proc1C10M-120GigE is a high-performance 100 GigE Vision frame grabber designed for real-time image acquisition, preprocessing, compression, and high-throughput data handling from high-speed 10 GigE Vision cameras in demanding multi-camera vision systems. Built on Gidel’s Proc10M FPGA module with Altera Stratix 10 MX FPGA technology, it delivers 10× higher DRAM and SRAM bandwidth than conventional DDR4 and QDR solutions. As a result, it can capture, process, and manage data from up to 12 × 10 GigE Vision channels, making it ideal for demanding industrial, scientific, and mission-critical imaging systems. Twelve 10 GigE Vision Acquisition with Real-Time FPGA Image Processing The Proc1C10M-120GigE is available as a plug-and-play 120 GigE Vision frame grabber or as part of a complete imaging & vision system with real-time FPGA preprocessing, image enhancement, and compression options. The built-in FPGA can process image data during acquisition, before the data reaches the host PC. This helps reduce bandwidth, storage, and host processing load while preserving low-latency performance for high-speed camera streams. Optional FPGA processing includes Compression, HDR correction, Detection, and additional image enhancement modules. Real-Time FPGA Processing Helps Enable: Reduced bandwidth for high-throughput image acquisition Low-latency processing directly in the acquisition flow Extended recording time through real-time compression Lower host processing load by offloading selected tasks to the FPGA Custom image pipelines using Gidel IPs or user FPGA logic For the full list of available image processing and enhancement options, please refer to the Options tab. Flexible Operating Modes The Proc1C10M-120GigE supports two operating modes selectable via firmware: InfiniVision: Ideal for synchronized multi-camera setups, combining all camera data, including data acquired across multiple cards, into a single buffer with support for dynamic resolutions and formats. ProcFG: Tailored for precision applications, offering fixed frame sizes, pixel formats, and uncompressed ROI grabbing. As a result, the Proc1C10M-120GigE adapts to diverse workflows, supporting both synchronized multi-camera systems and streamlined single-camera operations. InfiniVision: Multi-Camera Acquisition and Synchronization Built on Gidel’s InfiniVision architecture, the Proc1C10M-120GigE addresses key multi-camera challenges, including synchronization, bandwidth, connectivity, and scalability. It supports acquisition from up to 12 × 10 GigE Vision cameras, while scalable multi-card configurations enable synchronized acquisition from 100+ cameras. A PCIe Gen3 x16 host interface provides ultra-fast data transfer, while high-bandwidth HBM2 and DDR4 memory help sustain acquisition and real-time FPGA processing under demanding loads. As a result, the Proc1C10M-120GigE delivers reliable performance in high-bandwidth, high-resolution imaging systems. SDK and Development Tools The Proc1C10M-120GigE is supported by Gidel’s SDK, featuring intuitive GUIs and APIs for streamlined integration. Additionally, the ProcVision Suite adds advanced FPGA programming, debugging, and validation tools, enabling developers to customize data flows, real-time processing, and compression pipelines with ease. Consequently, they can create optimized, application-specific solutions faster and with reduced risk. Why Choose the Proc1C10M-120GigE Frame Grabber? 100 GigE Vision FPGA frame grabber for high-speed multi-camera image acquisition Up to 120 Gb/s aggregate input bandwidth Scalable InfiniVision architecture for synchronized multi-camera systems Up to 400 Gb/s acquisition throughput through high-bandwidth QSFP interfaces Advanced SDK and ProcVision Suite for rapid development and integration Optional real-time FPGA processing, image enhancement, and compression IPs The Proc1C10M-120GigE is the ideal choice when your workload requires very high-speed GigE Vision acquisition, synchronized multi-camera operation, and reliable image transfer to a host PC. Related Products View the Full Range of PCIe GigE Vision Frame Grabbers View the FantoVision20-GigE: Edge AI GigE Vision System - Published: 2023-03-22 - Modified: 2026-08-14 - URL: https://gidel.com/product/proc1c10n-100-gige-vision-frame-grabber/ - Software Types: Imaging & Vision - Product categories: GigE Vision Frame Grabbers & Image Processing, Frame Grabbers & Image Processing, Modular Imaging Solutions, Development Tools for Imaging & Vision Applications, FPGA Image Compression IPs, GIL: FPGA Imaging Libraries (IPs), Low Latency Recording & Streaming Solutions, Image Acquisition Solutions: ProcFG vs InfiniVision 12 × 10 GigE AI Frame Grabber for GigE Vision Cameras The Proc1C10N-120GigE is a high-performance 100 GigE Vision frame grabber designed for real-time image acquisition, preprocessing, compression, and AI acceleration from high-speed 10 GigE Vision cameras in demanding multi-camera vision systems. Built on Gidel’s Proc10N FPGA module with Altera Stratix 10 NX FPGA technology, it integrates embedded Tensor Blocks and HBM2 memory, delivering up to 143 INT8 TOPS of AI processing performance. As a result, it can process and analyze data from up to 12 × 10 GigE Vision channels, making it ideal for advanced vision-based AI systems. Twelve 10 GigE Vision Acquisition with Real-Time FPGA Image Processing The Proc1C10N-120GigE is available as a plug-and-play GigE Vision frame grabber or as part of a complete imaging & vision system with real-time FPGA preprocessing, image enhancement, and compression options. The built-in FPGA can process image data and execute AI inference models during acquisition, before the data reaches the host PC. This helps reduce bandwidth, storage, and host processing load while preserving low-latency performance for high-speed, intelligent camera streams. Optional FPGA processing includes Deep Learning inference acceleration via hardware Tensor Blocks, Compression, HDR correction, Detection, and additional image enhancement modules. Real-Time FPGA Processing Helps Enable: Reduced bandwidth for high-throughput image acquisition Low-latency processing directly in the acquisition flow Extended recording time through real-time compression Lower host processing load by offloading selected tasks to the FPGA Custom image pipelines using Gidel IPs or user FPGA logic For the full list of available image processing and enhancement options, please refer to the Options tab. Flexible Operating Modes The Proc1C10N-120GigE supports two operating modes selectable via firmware: InfiniVision: Ideal for synchronized multi-camera setups, combining all camera data, including data acquired across multiple cards, into a single buffer with support for dynamic resolutions and formats. ProcFG: Tailored for precision applications, offering fixed frame sizes, pixel formats, and uncompressed ROI grabbing. As a result, the Proc1C10N-120GigE adapts to diverse workflows, supporting both synchronized multi-camera systems and streamlined single-camera operations. InfiniVision: Multi-Camera Acquisition and Synchronization Built on Gidel’s InfiniVision architecture, the Proc1C10N-120GigE addresses key multi-camera challenges, including synchronization, bandwidth, connectivity, and scalability. It supports acquisition from up to 12 × 10 GigE Vision cameras, while scalable multi-card configurations enable synchronized acquisition from 100+ cameras. A PCIe Gen3 x16 host interface provides ultra-fast data transfer, while high-bandwidth HBM2 and DDR4 memory help sustain acquisition and real-time FPGA processing under demanding loads. As a result, the Proc1C10N-120GigE delivers reliable performance in high-bandwidth, AI-driven imaging systems. SDK and Development Tools The Proc1C10N-120GigE is supported by Gidel’s SDK, featuring intuitive GUIs and APIs for streamlined integration. Additionally, the ProcVision Suite adds advanced FPGA programming, debugging, and validation tools, enabling developers to customize data flows, real-time processing, and compression pipelines with ease. Consequently, they can create optimized, application-specific solutions faster and with reduced risk. Why Choose the Proc1C10N-120GigE Frame Grabber? 100 GigE Vision FPGA frame grabber for high-speed multi-camera image acquisition Up to 120 Gb/s aggregate input bandwidth Embedded AI Tensor Blocks for acceleration and inference Scalable InfiniVision architecture for synchronized multi-camera systems Up to 400 Gb/s acquisition throughput through high-bandwidth QSFP interfaces Advanced SDK and ProcVision Suite for rapid development and integration Optional real-time FPGA processing, image enhancement, and compression IPs The Proc1C10N-120GigE is the ideal choice when your workload requires very high-speed GigE Vision acquisition, synchronized multi-camera operation, and FPGA-based acceleration for AI-driven imaging workflows. Related Products View the Full Range of PCIe GigE Vision Frame Grabbers View the FantoVision20-GigE: Edge AI GigE Vision System - Published: 2023-03-21 - Modified: 2026-08-14 - URL: https://gidel.com/product/camera-link-frame-grabber/ - Software Types: Imaging & Vision - Product categories: Frame Grabbers & Image Processing, Camera Link Frame Grabbers & Image Processing, Modular Imaging Solutions, Development Tools for Imaging & Vision Applications, FPGA Image Compression IPs, GIL: FPGA Imaging Libraries (IPs), Low Latency Recording & Streaming Solutions, Image Acquisition Solutions: ProcFG vs InfiniVision High-Performance Frame Grabber for Camera Link Cameras The HawkEye-CL is a high-performance Camera Link frame grabber designed for real-time acquisition and FPGA-based image processing in demanding vision systems. Powered by the Altera Arria 10 FPGA, it is fully compliant with Camera Link Rev. 2. 0 and supports Camera Link 80-bit (Deca) acquisition with up to 17 GB of on-board memory and PCIe Gen3 x8 host connectivity. As a result, it delivers industry-leading bandwidth and reliability for applications where speed and precision are critical. Camera Link Acquisition with Real-Time FPGA Image Processing The HawkEye-CL is available as a plug-and-play CL frame grabber or as part of a complete imaging & vision system with real-time FPGA preprocessing, image enhancement, and compression options. The built-in FPGA can process image data during acquisition, before it reaches the host PC. This helps reduce bandwidth, storage, and host processing load while preserving low-latency performance for high-speed camera streams. Optional FPGA processing includes Compression, HDR correction, Detection, and additional image enhancement modules. Real-Time FPGA Processing Helps Enable: Reduced bandwidth for high-throughput image acquisition Low-latency processing directly in the acquisition flow Extended recording time through real-time compression Lower host processing load by offloading selected tasks to the FPGA Custom image pipelines using Gidel IPs or user FPGA logic For the full list of available image processing and enhancement options, please refer to the Options tab. Flexible Operating Modes The HawkEye-CL supports two operating modes selectable via firmware: InfiniVision: Ideal for synchronized multi-camera setups, combining all camera data, including data acquired across multiple cards, into a single buffer with support for dynamic resolutions and formats. ProcFG: Tailored for precision applications, offering fixed frame sizes, pixel formats, and uncompressed ROI grabbing. As a result, the HawkEye-CL adapts to diverse workflows, supporting both complex multi-camera systems and streamlined single-camera operations. InfiniVision: Multi-Camera Acquisition and Synchronization Built on Gidel’s InfiniVision architecture, the HawkEye-CL addresses key multi-camera challenges, including synchronization, bandwidth, connectivity, and scalability. Its FPGA-based design enables deterministic data handling and real-time preprocessing across demanding Camera Link acquisition workflows. A PCIe Gen3 x8 host interface provides CPU-free, ultra-fast data transfer, while on-board buffers of up to 17 GB support stable acquisition. As a result, the HawkEye-CL delivers reliable performance in high-speed, high-resolution vision systems. SDK and Development Tools The HawkEye-CL is supported by Gidel’s SDK, featuring intuitive GUIs and APIs for streamlined integration. Additionally, the ProcVision Suite adds advanced FPGA programming, debugging, and validation tools, enabling developers to customize data flows, real-time processing, and compression pipelines with ease. Consequently, they can create optimized, application-specific solutions faster and with reduced risk. Why Choose the HawkEye-CL Frame Grabber? Camera Link Rev. 2. 0 FPGA frame grabber with 80-bit Deca acquisition Up to 6. 8 Gb/s input bandwidth FPGA architecture for low-latency acquisition, processing, recording, and streaming Flexible operating modes for multi-camera and precision setups Advanced SDK and ProcVision Suite for rapid development and integration Optional real-time FPGA processing, image enhancement, and compression IPs The HawkEye-CL is the ideal choice when your workload requires high-speed Camera Link acquisition, low-latency FPGA processing, and reliable image transfer to a host PC. Related Products View the FantoVision20-CL: Edge AI Camera Link System View the Camera Link Simulator - Published: 2023-03-21 - Modified: 2026-08-14 - URL: https://gidel.com/product/proc10a-cxp-6-frame-grabber/ - Software Types: Imaging & Vision - Product categories: CoaXPress Frame Grabbers & Image Processing, Frame Grabbers & Image Processing, Modular Imaging Solutions, FPGA Image Compression IPs, GIL: FPGA Imaging Libraries (IPs), Low Latency Recording & Streaming Solutions, Image Acquisition Solutions: ProcFG vs InfiniVision 8-Link CXP-6 Frame Grabber for CoaXPress Cameras The Proc10A-CXP is a high-performance eight-link CXP-6 frame grabber designed for real-time image acquisition, preprocessing, and compression from high-speed CoaXPress-6 cameras in demanding multi-camera vision systems. Powered by Altera Arria 10 FPGA technology, it supports 8 × CXP-6 links with up to 50 Gb/s aggregate input bandwidth. As a result, it delivers zero-frame-loss acquisition, ultra-low latency, and negligible host CPU load for high-speed and mission-critical imaging applications. Octo CXP-6 Acquisition with Real-Time FPGA Image Processing The Proc10A-CXP is available as a plug-and-play CXP frame grabber or as part of a complete imaging & vision system with real-time FPGA preprocessing, image enhancement, and compression options. The built-in FPGA can process image data during acquisition, before it reaches the host PC. This helps reduce bandwidth, storage, and host processing load while preserving low-latency performance for high-speed camera streams. Optional FPGA processing includes Compression, HDR correction, Detection, and additional image enhancement modules. Real-Time FPGA Processing Helps Enable: Reduced bandwidth for high-throughput image acquisition Low-latency processing directly in the acquisition flow Extended recording time through real-time compression Lower host processing load by offloading selected tasks to the FPGA Custom image pipelines using Gidel IPs or user FPGA logic For the full list of available image processing and enhancement options, please refer to the Options tab. Flexible Operating Modes The Proc10A-CXP supports two operating modes selectable via firmware: InfiniVision: Ideal for synchronized multi-camera setups, combining all camera data, including data acquired across multiple cards, into a single buffer with support for dynamic resolutions and formats. ProcFG: Optimized for line-scan applications, offering fixed frame sizes, pixel formats, and uncompressed ROI grabbing. As a result, the Proc10A-CXP adapts to diverse workflows, supporting both synchronized multi-camera systems and streamlined single-camera operations. InfiniVision: Multi Camera Acquisition and Synchronization Built on Gidel’s InfiniVision architecture, the Proc10A-CXP addresses key multi-camera challenges, including synchronization, bandwidth, connectivity, and scalability. It supports up to eight CXP-6 links, enabling simultaneous acquisition from one to eight cameras, depending on the number of links required by each camera. A PCIe Gen3 x8 host interface provides CPU-free, ultra-fast data transfer, while on-board buffers of up to 33 GB support stable acquisition and real-time FPGA image processing. As a result, the Proc10A-CXP delivers reliable performance in high-speed, high-resolution imaging systems. SDK and Development Tools The Proc10A-CXP is supported by Gidel’s SDK, featuring intuitive GUIs and APIs for easy integration. Moreover, the ProcVision Suite adds advanced FPGA programming, debugging, and validation tools, enabling rapid customization of data pipelines, real-time processing, and compression workflows. Consequently, developers can deploy optimized, application-specific solutions faster and with reduced risk. Why Choose the Proc10A-CXP Frame Grabber? Octo CXP-6 FPGA frame grabber for high-speed multi-camera image acquisition Up to 50 Gb/s aggregate input bandwidth FPGA architecture for low-latency acquisition, processing, recording, and streaming Flexible operating modes for multi-camera and precision setups Advanced SDK and ProcVision Suite for rapid development and integration Optional real-time FPGA processing, image enhancement, and compression IPs The Proc10A-CXP is the ideal choice when your workload requires high-bandwidth CXP-6 acquisition, low-latency FPGA processing, and reliable image transfer to a host PC. Related ProductsView the Full Range of PCIe CoaXPress Frame Grabbers View the FantoVision40-CXP12: Edge AI CoaXPress System View the CoaXPress Camera Simulator - Published: 2023-03-21 - Modified: 2026-08-14 - URL: https://gidel.com/product/hawkeye-coaxpress-12-frame-grabber/ - Software Types: Imaging & Vision - Product categories: CoaXPress Frame Grabbers & Image Processing, Frame Grabbers & Image Processing, Modular Imaging Solutions, Development Tools for Imaging & Vision Applications, FPGA Image Compression IPs, GIL: FPGA Imaging Libraries (IPs), Low Latency Recording & Streaming Solutions, Image Acquisition Solutions: ProcFG vs InfiniVision 4-Link CXP-12 Frame Grabber for CoaXPress Cameras The HawkEye-CXP12 is a high-performance four-link CoaXPress-12 frame grabber designed for real-time image acquisition, preprocessing, and compression from high-speed CoaXPress-12 cameras in demanding multi-camera vision systems. Powered by Altera Arria 10 FPGA technology, it supports 4 × CXP-12 links with up to 50 Gb/s aggregate input bandwidth. As a result, it delivers zero-frame-loss acquisition, ultra-low latency, and negligible host CPU load for high-speed and mission-critical imaging applications. Quad CXP-12 Acquisition with Real-Time FPGA Image Processing The HawkEye-CXP12 is available as a plug-and-play CoaXPress frame grabber or as part of a complete imaging & vision system with real-time FPGA preprocessing, image enhancement, and compression options. The built-in FPGA can process image data during acquisition, before it reaches the host PC. This helps reduce bandwidth, storage, and host processing load while preserving low-latency performance for high-speed camera streams. Optional FPGA processing includes Compression, HDR correction, Detection, and additional image enhancement modules. Real-Time FPGA Processing Helps Enable: Reduced bandwidth for high-throughput image acquisition Low-latency processing directly in the acquisition flow Extended recording time through real-time compression Lower host processing load by offloading selected tasks to the FPGA Custom image pipelines using Gidel IPs or user FPGA logic For the full list of available image processing and enhancement options, please refer to the Options tab. Flexible Operating Modes The HawkEye-CXP12 can switch between InfiniVision Mode and ProcFG Mode via firmware update: InfiniVision: Ideal for synchronized multi-camera setups, combining all camera data, including data acquired across multiple cards, into a single buffer with support for dynamic resolutions and formats. ProcFG: Optimized for line-scan applications, offering fixed frame sizes, pixel formats, and uncompressed ROI grabbing. As a result, the HawkEye-CXP12 adapts to diverse workflows, supporting both synchronized multi-camera systems and streamlined single-camera operations. InfiniVision: Multi-Camera Acquisition and Synchronization Built on Gidel’s InfiniVision architecture, the HawkEye-CXP12 addresses key multi-camera challenges, including synchronization, bandwidth, connectivity, and scalability. It supports up to four CXP-12 links, enabling simultaneous acquisition from one to four cameras, depending on the number of links required by each camera. A PCIe Gen3 x8 host interface provides CPU-free, ultra-fast data transfer, while on-board buffers of up to 17 GB support stable acquisition and real-time FPGA image processing. As a result, the HawkEye-CXP12 delivers reliable performance in high-speed, high-resolution imaging systems. SDK and Development Tools The HawkEye-CXP12 is supported by Gidel’s SDK, which includes intuitive GUIs and APIs for streamlined integration. In addition, the ProcVision Suite provides FPGA programming, debugging, and validation tools, enabling rapid customization of data flows, image processing, and compression pipelines. Consequently, developers can create optimized, application-specific solutions faster and with reduced risk. Why Choose the HawkEye-CXP12 Frame Grabber? Quad CXP-12 FPGA frame grabber for high-speed multi-camera image acquisition Up to 50 Gb/s aggregate input bandwidth FPGA architecture for low-latency acquisition, processing, recording, and streaming Flexible operating modes for multi-camera and precision setups Advanced SDK and ProcVision Suite for rapid development and integration Optional real-time FPGA processing, image enhancement, and compression IPs The HawkEye-CXP12 is the ideal choice when your workload requires high-bandwidth CXP-12 acquisition, low-latency FPGA processing, and reliable image transfer to a host PC. Related ProductsView the Full Range of PCIe CoaXPress Frame Grabbers View the FantoVision40-CXP12: Edge AI CoaXPress System View the CoaXPress Camera Simulator - Published: 2023-03-21 - Modified: 2026-06-12 - URL: https://gidel.com/product/fpga-accelerator-card/ - Software Types: FPGA Compute Acceleration - Product categories: FPGA Compute Acceleration Boards Proc10A: High-Performance FPGA Accelerator Card The Proc10A™ is a flexible, high-performance, low-power FPGA accelerator card built on Altera’s Arria® 10 FPGA. Designed for networking, and demanding data-processing workloads, it not only delivers robust computing power but also ensures excellent energy efficiency, making it ideal for modern systems. FPGA Accelerator Card Architecture and Memory Capabilities With up to fifteen 14. 2 Gb/s full-duplex transceivers and extensive memory options, the Proc10A FPGA accelerator card delivers outstanding I/O throughput and on-board processing performance. Additionally, its multi-level memory architecture includes: Up to 32 GB DDR3 ECC SODIMM for high-capacity requirements. On-board 1 GB DDR3 SDRAM for low-latency local operations. Dedicated FPGA memory blocks (M20K and MLABs) for real-time data handling. As a result, the Proc10A is particularly effective for low-latency, high-bandwidth storage, networking, and advanced imaging applications. In addition, its architecture enables engineers to meet demanding performance goals without sacrificing efficiency. High-Speed Connectivity in a Compute Accelerator The Proc10A integrates an 8-lane PCI Express Gen3 bridge, enabling fast and efficient co-processing between the host CPU and the FPGA. Furthermore, for applications requiring tightly coupled FPGA-CPU functionality, the Proc10A SoC family includes an embedded ARM processor based on Arria® 10 SoC FPGAs, providing developers with even greater design flexibility. Consequently, the Proc10A supports a wide range of high-performance, mission-critical applications. Development Tools for High-Performance FPGA Platforms Supported by Gidel’s advanced development suite, the Proc10A FPGA accelerator card simplifies integration and accelerates deployment. Moreover, it supports C and HDL-based workflows, reducing engineering time, improving system reliability, and shortening time-to-market. Therefore, teams can bring powerful FPGA-based solutions to market faster and with greater confidence. Why Choose the Proc10A FPGA Accelerator Card? Built on Altera Arria® 10 FPGA for reliable, proven performance. Up to 15 full-duplex 14. 2 Gb/s transceivers for high-speed data processing. Multi-level memory architecture with up to 32 GB DDR3 ECC SODIMM. PCIe Gen3 x8 connectivity for seamless FPGA-CPU interaction. SoC variant with ARM processor for tightly coupled processing. Backed by Gidel’s development tools, ensuring faster and more efficient delivery. For more accelerator card options, visit FPGA Compute Acceleration - Gidel Target applications: DSP (Digital Signal Processing) and HPRC (High Performance Reconfigurable Computing) High-speed, Low-latency Networking and Network Analysis Life Science Applications Linear Algebra and 3D Applications Computational Finance and HFT Data Analytics Deep Packet Inspection Surveillance, Machine Vision, and Imaging High Performance Acquisition Systems - Published: 2022-07-27 - Modified: 2026-08-14 - URL: https://gidel.com/product/jetson-frame-grabber/ - Software Types: FantoVision40 - Product categories: GigE Vision Frame Grabbers & Image Processing, CoaXPress Frame Grabbers & Image Processing, Modular Imaging Solutions, Development Tools for Imaging & Vision Applications, FPGA Image Compression IPs, GIL: FPGA Imaging Libraries (IPs), Low Latency Recording & Streaming Solutions, Image Acquisition Solutions: ProcFG vs InfiniVision, Aerial Mapping ISP: SkyBoost-RT vs. SkyBoost, FantoVision40 Edge AI with FPGA Frame Grabbers, FantoVision Edge AI with FPGA Frame Grabbers Jetson with CoaXPress-12 & 10 GigE Frame Grabbers The FantoVision40 is a rugged Jetson frame grabber system with fully integrated CoaXPress-12 and GigE Vision acquisition. Powered by the NVIDIA Jetson Orin NX, it simultaneously captures and processes data from up to 4 × CoaXPress 2. 1 (CXP-12) links in real time with PoCXP, with an option for up to 4 × 10 GigE Vision cameras. It combines high-end image acquisition on an Arria 10™ FPGA with real-time GPU processing on Jetson, enabling low-latency recording, streaming, and Edge AI in an ultra-compact, low-SWaP form factor. Jetson CXP-12 & GigE Vision Acquisition with Real-Time FPGA Image Processing The FantoVision40 is available as a plug-and-play dual-interface frame grabber system supporting CoaXPress and GigE Vision acquisition, or as part of a complete imaging & vision solution with real-time FPGA preprocessing, image enhancement, and compression options. The built-in FPGA can process image data during acquisition, before the data reaches the Jetson module. This helps reduce bandwidth, storage, and Jetson processing load while preserving low-latency performance for high-speed camera streams. Optional FPGA processing includes Compression, HDR correction, Detection, and additional image enhancement modules. Real-Time FPGA Processing Helps Enable: Reduced bandwidth for high-throughput image acquisition Low-latency processing directly in the acquisition flow Extended recording time through real-time compression Lower Jetson processing load by offloading selected tasks to the FPGA Custom image pipelines using Gidel IPs or user FPGA logic For the full list of available image processing and enhancement options, please refer to the Options tab. Flexible Development Tools Open architecture: split/chain processing between FPGA and GPU GPU development: CUDA | C/C++ and NVIDIA AI libraries on Jetson FPGA development: rapid pre‑processing deployment with ProcVision Suite Integrated Vision Acquisition and Processing Deploy a single compact Jetson + FPGA node for CXP and GigE Vision camera acquisition, real-time preprocessing, Edge AI inference, recording, and streaming. This approach reduces cabling, latency, and overall system cost while improving reliability and maintainability. For large-scale, synchronized camera deployments, Gidel’s InfiniVision multi-camera vision system enables synchronization and processing across 100+ sensors within a flexible acquisition framework. For applications that require strict determinism, line-scan optimization, or guaranteed frame capture with fixed timing, ProcFG provides a dedicated deterministic image acquisition layer. Both approaches integrate seamlessly into Gidel’s FPGA-based vision platforms and scale from single-node systems to multi-unit topologies. Why Choose the FantoVision40? Compact NVIDIA Jetson + FPGA system with integrated Quad CXP-12 frame grabber PoCXP support for long-reach, robust camera connectivity Optional Quad 10 GigE Vision interface for flexible Ethernet camera integration Up to 50 Gb/s aggregate interface bandwidth FPGA + GPU architecture for low-latency acquisition, processing, recording, streaming, and Edge AI Optional real-time FPGA image processing, enhancement, and compression IPs The FantoVision40 is the ideal choice when you need simultaneous CoaXPress and 10 GigE camera acquisition in a compact, low-latency Jetson platform. Related ProductsView the Full FantoVision System RangeView the Full Range of PCIe CoaXPress Frame Grabbers View the Full Range of PCIe GigE Vision Frame Grabbers View the CoaXPress Camera Simulator - Published: 2022-07-23 - Modified: 2026-08-14 - URL: https://gidel.com/product/jetson-dual-interface-frame-grabber/ - Software Types: FantoVision20 - Product categories: FantoVision20 Edge AI with FPGA Frame Grabbers, GigE Vision Frame Grabbers & Image Processing, Camera Link Frame Grabbers & Image Processing, Modular Imaging Solutions, Development Tools for Imaging & Vision Applications, FPGA Image Compression IPs, GIL: FPGA Imaging Libraries (IPs), Low Latency Recording & Streaming Solutions, Image Acquisition Solutions: ProcFG vs InfiniVision, Aerial Mapping ISP: SkyBoost-RT vs. SkyBoost, FantoVision Edge AI with FPGA Frame Grabbers Jetson with 10 GigE Vision & Camera Link Frame Grabbers The FantoVision20 is a rugged Jetson system with a fully integrated dual interface frame grabber. Powered by the NVIDIA Jetson Orin NX or Xavier NX, it simultaneously captures and processes data from up to 2 × 10 GigE Vision cameras and from Camera Link Deca, Full, Medium, Base, or Dual Base camera configurations. It combines high-end image acquisition on an Arria 10™ FPGA with real-time GPU processing on Jetson, enabling low-latency recording, streaming, and Edge AI in an ultra-compact, low-SWaP form factor. Jetson GigE Vision & Camera Link Acquisition with Real-Time FPGA Image Processing The FantoVision20 is available as a plug-and-play dual-interface frame grabber system supporting GigE Vision and Camera Link acquisition, or as part of a complete imaging & vision solution with real-time FPGA preprocessing, image enhancement, and compression options. The built-in FPGA can process image data during acquisition, before the data reaches the Jetson module. This helps reduce bandwidth, storage, and Jetson processing load while preserving low-latency performance for high-speed camera streams. Optional FPGA processing includes Compression, HDR correction, Detection, and additional image enhancement modules. Real-Time FPGA Processing Helps Enable: Reduced bandwidth for high-throughput image acquisition Low-latency processing directly in the acquisition flow Extended recording time through real-time compression Lower Jetson processing load by offloading selected tasks to the FPGA Custom image pipelines using Gidel IPs or user FPGA logic For the full list of available image processing and enhancement options, please refer to the Options tab. Flexible Development Tools Open architecture: split/chain processing between FPGA and GPU GPU development: CUDA | C/C++ and NVIDIA AI libraries on Jetson FPGA development: rapid pre‑processing deployment with ProcVision Suite Integrated Vision Acquisition and Processing Deploy a single compact Jetson + FPGA node for Camera Link and GigE camera acquisition, real-time preprocessing, Edge AI inference, recording, and streaming. This approach reduces cabling, latency, and overall system cost while improving reliability and maintainability. For large-scale, synchronized camera deployments, Gidel’s InfiniVision multi-camera vision system enables synchronization and processing across 100+ sensors within a flexible acquisition framework. For applications that require strict determinism, line-scan optimization, or guaranteed frame capture with fixed timing, ProcFG provides a dedicated deterministic image acquisition layer. Both approaches integrate seamlessly into Gidel’s FPGA-based vision platforms and scale from single-node systems to multi-unit topologies. Why Choose the FantoVision20? Compact NVIDIA Jetson + FPGA system with integrated 10 GigE Vision and Camera Link frame grabber Up to 26. 8 Gb/s aggregate input bandwidth FPGA + GPU architecture for low-latency acquisition, processing, recording, streaming, and Edge AI Optional real-time FPGA image processing, enhancement, and compression IPs The FantoVision20 is the ideal choice when you need simultaneous GigE Vision and Camera Link camera acquisition in a compact, low-latency Jetson platform. Related ProductsView the Full FantoVision System RangeView the Full Range of PCIe GigE Vision Frame Grabbers View the PCIe Camera Link Frame Grabber View the Camera Link Simulator ## Applications - Published: 2025-06-16 - Modified: 2026-07-06 - URL: https://gidel.com/application/drone-computer/ Drone Computer for Imaging & Vision Applications A drone computer must process data instantly. UAV missions demand low latency and high reliability. Therefore, Gidel FantoVision edge computers are built for real-time imaging at the edge. They combine a compact form factor, rugged construction, and FPGA-accelerated processing. As a result, UAVs can make fast decisions in the air. High-Bandwidth Multi-Camera Support Our Low SWaP systems are 13. 4 × 9 × 6 cm and 750 g. They fit easily into multirotor, fixed wing, and VTOL platforms. They also support 10GigE Vision, CoaXPress, and Camera Link. This enables synchronized multi-camera capture up to 40 Gb/s throughput. Therefore, they are ideal for: High-resolution imaging workflows Aerial inspection and surveying Real-time mapping and 3D reconstruction Situational awareness, defense, and ISR Search and rescue and environmental monitoring FPGA + AI Hybrid Edge Processing in Drone Computers FPGA pipelines handle deterministic real-time data flow while the NVIDIA Jetson performs onboard AI inference. This heterogeneous approach is designed to overcome common UAV vision bottlenecks such as excessive CPU load, unpredictable latency, bandwidth saturation between processing stages, and limited scalability as camera count or resolution increases. Up to 2 TB internal storage supports long autonomous missions and extended data capture when required. Flexible Drone Computer Architecture and Real-Time Image Enhancement All image signal processing runs inline on the FPGA to preserve deterministic, low-latency behavior. This includes debayering, non-uniformity correction (NUC), bad pixel correction (BPC), white balance, gamma correction, and dynamic luminance balancing. Gidel’s real-time HDR processing enhances visibility and contrast under challenging lighting conditions. To optimize bandwidth and storage, the FPGA also supports real-time data reduction using JPEG, Lossless, and Quality+ compression, along with region-of-interest extraction and scaling. These capabilities reduce data movement and prevent downstream processing bottlenecks without compromising image quality. Development and customization are supported through Gidel’s Software Development Tools, which enable developers to design, integrate, and optimize FPGA-based imaging and vision pipelines while maintaining full control over latency, determinism, and system behavior. Gidel provides a scalable, low-latency drone computer for edge imaging. We also offer Mini Powerful FPGA modules for even tighter SWaP constraints or advanced customization. This gives UAV integrators full flexibility while ensuring mission success and real-time decision-making. Need more information? Full Name Email Phone - Published: 2024-12-08 - Modified: 2026-07-06 - URL: https://gidel.com/application/volumetric-imaging-augmented-reality/ Gidel provides a modular FPGA-based vision infrastructure designed to support real-time volumetric imaging and augmented reality applications. These systems enable synchronized capture and processing of data from multiple cameras. As a result, they can reconstruct three-dimensional scenes with high accuracy, low latency, and deterministic performance. Volumetric imaging places unique demands on vision architectures. In particular, multi-camera synchronization, sustained high bandwidth, and real-time processing must operate predictably. Otherwise, accurate 3D reconstruction and stable augmented reality overlays cannot be achieved. As system complexity grows, software-centric approaches often struggle to scale. Hardware Platforms for Volumetric Imaging & AR Gidel supports volumetric imaging system design with a portfolio of modular hardware building blocks. These offerings allow system integrators to tailor acquisition, processing, and deployment to the needs of each 3D capture and AR pipeline. A key component is Gidel’s InfiniVision multi-camera vision system. It enables deterministic grabbing and synchronization across large-scale camera arrays, including configurations exceeding 100 cameras. Depending on system requirements, developers can select from: High-Performance Frame Grabbers: For deterministic multi-camera acquisition. Mini Jetson Frame Grabbers: Combining Altera FPGA's and NVIDIA Jetson Orin NX for integrated processing at the source. Scalable FPGA Modules: For ultra-compact designs and deep customization. Real-Time FPGA Image Processing & Compression All FPGA processing runs inline to preserve low latency and predictable timing. This ensures image quality remains consistent across all views, which is essential for accurate volumetric alignment. Standard Processing Capabilities: Debayering, White Balance, and Gamma Correction. Non-Uniformity Correction (NUC) and Bad Pixel Correction (BPC). Dynamic Luminance Balancing and Real-Time HDR for mixed lighting. Bandwidth Optimization: To optimize storage, the FPGA supports real-time data reduction using JPEG, Lossless, and Quality+ compression, alongside region-of-interest extraction and scaling. High-Resolution Imaging with Deterministic Performance Volumetric imaging applications increasingly rely on high-resolution sensors to enable fine spatial detail and precise depth estimation. Gidel’s FPGA-based architecture handles these high-resolution workflows without introducing additional latency or timing jitter. By combining inline processing with deterministic data handling, the system maintains stable performance as image resolution and processing complexity increase. High-Bandwidth Recording Solutions Many volumetric imaging workflows require reliable recording of multi-camera streams for offline 3D reconstruction, algorithm validation, and post-session analysis. To address these needs, Gidel provides dedicated Recording Solutions. These recording platforms integrate with Gidel’s architecture to capture and store image streams deterministically, without disrupting real-time processing. As a result, volumetric imaging systems can support both live operation and high-quality offline reconstruction. Development Tools and Customization for volumetric imaging Development is supported through Gidel’s Software Development Tools. These tools enable developers to design, integrate, and optimize FPGA-based imaging pipelines. They provide fine-grained control over latency, data flow, and processing behavior, which is critical for advanced volumetric imaging and augmented reality systems. Need more information? Full Name Email Phone - Published: 2024-12-08 - Modified: 2026-06-23 - URL: https://gidel.com/application/sorting-machines/ Scalable Vision Architecture for Optical Sorting Machines Modern optical sorting machines depend on advanced vision architectures to deliver high accuracy and consistent performance. As production lines become faster and more complex, vision systems must support higher resolutions and tighter timing constraints. Consequently, fixed-function designs often struggle to scale or adapt over time. Modular Infrastructure for Optical Sorting Machines Gidel provides a flexible vision infrastructure that allows system designers to build, enhance, or upgrade optical sorting machines using modular building blocks. These architectures rely on high-performance Frame Grabbers, which provide deterministic image acquisition and stable real-time processing. As a result, system performance can scale over time without requiring a complete redesign, while preserving predictable behavior and long-term flexibility. Deterministic Vision Processing for High-Speed Sorting In high-speed sorting machines, latency and synchronization are critical. Vision systems must process image data in real time while maintaining deterministic behavior. Otherwise, even small timing variations can reduce sorting accuracy. Deterministic Processing at High Throughput Gidel’s FPGA-based vision architecture is designed for predictable, real-time image processing. Moreover, hardware-based Compression IPs reduce data bandwidth while preserving the image fidelity required for accurate decisions: JPEG Encoder: High-speed standard compression. Lossless Compression: Bit-perfect data preservation. Quality+ Compression: Optimized balance of ratio and quality. As a result, high-speed sorting machines can scale throughput while maintaining deterministic, low-latency operation. Compact Architectures for Embedded Sorting Systems For space- and power-constrained environments, Gidel also supports compact sorting platforms using Mini Jetson Frame Grabbers. These systems combine deterministic FPGA-based vision processing with NVIDIA Jetson Modules, allowing sorting machines to balance throughput, accuracy, and system footprint. Optical Inspection Architecture for Sorting Machines Many systems combine inspection and sorting within a single platform. An optical inspection machine typically performs image analysis, defect detection, or classification before triggering sorting actions. However, inspection workloads can interfere with real-time behavior if they are not carefully managed. Custom FPGA Algorithm Development To address this, Gidel enables a unified vision architecture where inspection and sorting coexist efficiently. System designers can design, develop, and deploy custom imaging and vision algorithms directly on the FPGA using the ProcVision Suite. This approach provides full control over latency, precision, and processing flow. As a result, optical inspection machines can implement proprietary algorithms, optimize performance for specific materials or products, and maintain deterministic behavior even in demanding, high-speed environments. Learn more about Gidel’s real-world advantages in High-Speed AOI Machines: Enabling High-Speed AOI Machines | Gidel Need more information? Full Name Email Phone - Published: 2024-12-05 - Modified: 2026-06-23 - URL: https://gidel.com/application/modular-medical-imaging/ https://youtu. be/wv3dPIv_4Cg Gidel delivers advanced medical imaging solutions built on FPGA-based image acquisition and processing architectures. These solutions address the demanding requirements of modern medical imaging systems, where real-time performance, high data throughput, and deterministic behavior are critical. By combining high-speed image acquisition, efficient memory management, and flexible processing pipelines, Gidel enables medical imaging systems to deliver precise, reliable, and actionable imaging results for clinical use. Gidel’s portfolio includes high-performance Frame Grabbers, Mini Jetson Frame Grabbers, and Powerful Mini FPGA Modules designed for embedded and clinical environments. Why FPGA Technology Matters in Medical Imaging Medical imaging applications demand consistent low latency, high-resolution data handling, and predictable system behavior. Gidel’s FPGA-based solutions provide real-time processing, high-throughput data handling, and a flexible architecture that integrates seamlessly into diverse medical imaging platforms. As a result, system designers can meet strict performance, reliability, and regulatory requirements while maintaining long-term system stability, even when working with multi-sensor, high-bandwidth imaging modalities. High-Resolution Imaging with Minimal Latency One of the key advantages of Gidel’s technology is its ability to handle high-resolution imaging data with minimal latency. This capability ensures the delivery of high-quality video streams that are essential for diagnostics, monitoring, and image-guided procedures. Gidel’s architectures support advanced imaging features such as HDR processing, real-time overlays, and feature extraction, all of which play a central role in modern medical imaging workflows. Compact and Power-Efficient System Design Gidel’s solutions combine a compact form factor with low power consumption, making them well suited for space-constrained and energy-sensitive environments. These include operating rooms, mobile imaging carts, and portable medical devices where thermal management and system size are critical. Mini FPGA modules and embedded vision platforms enable deterministic performance while meeting tight SWaP constraints. Real-World Medical Imaging Applications Advanced Diagnostic Imaging Devices In diagnostic imaging systems such as CT and MRI, Gidel’s technology accelerates image reconstruction by enabling high-speed data transfer and parallel processing. This improves overall system throughput and reduces the time required to generate clear, high-quality diagnostic images. ThermoMind Case Study – Early Breast Cancer Detection Multimodal, Radiation-Free Screening: ThermoMind’s Vision One device combines infrared, depth sensing, and AI to detect physiological changes linked to early-stage breast cancer. The system captures over 300 data points per scan and operates with no radiation, no contact, and no invasive procedures. High-Bandwidth Real-Time Imaging: Powered by Gidel’s FantoVision40-CXP12 edge computer and FPGA-based frame grabbers, the system acquires and processes multiple high-resolution sensor streams simultaneously. Up to 15 sensors capture data at 30–60 fps, while real-time FPGA Compression IPs eliminate acquisition bottlenecks. Compact, Deployable Medical Platform: This mini system architecture enables easy integration into space-constrained medical environments. Its performance and efficiency support global deployment, including multi-center clinical trials with leading medical institutions. Read the full article: Revolutionizing Breast Cancer Screening Device Laparoscopic Visualization Systems Gidel’s Proc10A-40GigE platform supports advanced laparoscopic systems such as 270 Surgical’s SURROUND SCOPE™, which provides a 270-degree field of view. Through efficient DRAM utilization, real-time image overlays, and uncompressed 4K video output over 12G-SDI, Gidel’s solution enhances surgical visualization and intraoperative decision-making. Real-Time Image-Guided Surgery Gidel’s medical imaging solutions enable real-time image overlays that assist surgeons during complex procedures. The FPGA-based architecture ensures deterministic, low-latency feedback, which is essential for maintaining precision and reducing procedural risk. Mini Jetson Frame Grabbers enable tight integration between image acquisition, FPGA processing, and GPU-based AI inference. Reliable Medical Imaging Solutions from Gidel System developers achieve greater efficiency by integrating Gidel’s customizable medical imaging solutions. These include frame grabbers, Mini Jetson Frame Grabbers, and compact FPGA modules. These capabilities contribute to improved patient outcomes and enhanced healthcare delivery Gidel’s Software Development Tools simplify system integration and FPGA configuration. This enables faster development cycles and easier long-term maintenance of medical imaging systems. Need more information? Full Name Email Phone - Published: 2023-03-28 - Modified: 2026-06-23 - URL: https://gidel.com/application/embedded-fpga-solutions-for-embedded-vision/ Gidel’s embedded FPGA solutions address the growing demand for high-performance, compact, and power-efficient embedded systems. Gidel delivers a broad portfolio of modular embedded FPGA platforms, combining compact hardware building blocks with advanced software tools to support a wide range of embedded vision and computing applications. As a market leader in FPGA architectures and algorithms, Gidel enables both rapid deployment using off-the-shelf solutions and deeper customization for advanced users. Embedded Vision Applications Enabled by Embedded FPGA As processors become more powerful and increasingly miniaturized, Embedded Vision systems continue to expand into new application domains. These include industrial automation, automotive systems, drones, robotics, and portable devices. Thanks to advances in Embedded Computing and AI, applications that once required stationary and power-hungry PCs can now operate at the edge, integrated directly into vehicles, mobile platforms, or compact devices. Real-Time Image Processing IPs In many embedded vision systems, image quality and bandwidth efficiency are critical. Gidel provides a range of hardware-based Compression IPs optimized for real-time embedded imaging: JPEG Encoder: High-performance standard compression. Lossless Compression: Perfect preservation of raw data. Quality+ Compression: Efficient data reduction without compromising image fidelity. HDR IP: Real-time contrast enhancement for dynamic lighting conditions. Design Constraints in Embedded FPGA Systems Designers of embedded vision systems face strict constraints that drive system architecture decisions: SWaP (Size, Weight, and Power): Keeping systems compact and battery-friendly. Thermal Efficiency: Managing heat in enclosed spaces. Bandwidth: Handling massive data flows between internal hardware and the cloud. Gidel Embedded FPGA Platforms With more than 30 years of expertise in FPGA development and acceleration, Gidel helps system designers overcome these challenges. Gidel’s Embedded FPGA Modules and heterogeneous platforms provide deterministic performance while meeting tight SWaP budgets. Embedded Vision and AI at the Edge For edge vision and AI workloads, Gidel also offers Mini Jetson Frame Grabbers that tightly integrate embedded FPGA processing with GPU-based AI acceleration. Software Tools and Customization To further simplify development, Gidel provides comprehensive Software Development Tools that streamline FPGA programming, system integration, and performance optimization. Together, these embedded FPGA solutions enable faster development cycles, scalable system designs, and reliable deployment of embedded vision and AI systems at the edge. Need more information? Full Name Email Phone - Published: 2023-03-27 - Modified: 2026-06-23 - URL: https://gidel.com/application/defense-imaging-solutions/ Gidel builds FPGA-based defense imaging solutions on a modular vision architecture that supports high-performance, mission-critical defense applications. These systems deliver deterministic behavior, high accuracy, and real-time responsiveness in demanding operational environments. Defense imaging systems must operate with extreme reliability while processing large volumes of visual data under strict timing constraints. They also need to remain adaptable, maintainable, and cost-effective throughout long deployment lifecycles. For this reason, modern defense platforms rely on scalable architectures that can evolve without complete system redesigns or extensive retraining. Gidel provides a flexible FPGA-based infrastructure for imaging and vision applications that require real-time image acquisition, processing, and signal handling. These capabilities support a wide range of defense systems, including surveillance, tracking, targeting, and secure communications. In these environments, predictable performance and long-term system stability are essential. Modular Vision Platforms for Defense Imaging Gidel structures its defense imaging infrastructure around modular building blocks that system designers can combine and scale to meet specific requirements: Edge AI Vision Computers: Compact, ruggedized systems for onsite inference combining Altera FPGA and NVIDIA Jetson modules. High-Performance Frame Grabbers: Supporting GigE Vision, CoaXPress, and Camera Link. Mini Powerful FPGA Modules: For tight SWaP constraints. Together, they support real-time, high-resolution vision pipelines in constrained environments. This modular approach allows defense imaging systems to scale, upgrade, or extend functionality as mission requirements evolve, without disrupting existing system behavior. Development Ecosystem and Long-Term System Flexibility To support efficient development and long-term maintainability, Gidel provides a comprehensive Software Development Tools ecosystem based on a modular design philosophy. This environment lets developers offload pixel-intensive image signal processing tasks to the FPGA. As a result, systems reduce CPU load and maintain deterministic real-time behavior. Using this approach, developers can assemble imaging and vision pipelines with real-time image processing functions executed inline on the FPGA: Preprocessing: Debayering, White Balance, and Gamma Correction. Correction: Non-Uniformity Correction (NUC) and Bad Pixel Replacement (BPR). Enhancement: Dynamic Luminance Balancing and real-time HDR processing. In addition, optional data optimization features such as Compression IPs (JPEG, Lossless, and Quality+), region-of-interest cropping, and scaling help defense imaging systems manage bandwidth and storage efficiently. High-Bandwidth Recording Solutions for Defense Applications Many defense imaging systems require reliable recording of high-resolution, high-frame-rate data for post-mission analysis, validation, and evidence retention. Common use cases include: ISR missions Multi-sensor fusion and tracking Target acquisition and assessment High-bandwidth recording for post-mission analysis To support these needs, Gidel provides dedicated Recording Solutions for high-bandwidth defense imaging workflows. These recording platforms integrate with Gidel’s modular FPGA-based vision architecture to capture and store high-rate image streams while preserving predictable system behavior. By combining real-time processing, optional data optimization, and scalable recording capabilities, Gidel supports both live operation and detailed offline analysis without disrupting the real-time imaging pipeline. Need more information? Full Name Email Phone - Published: 2023-03-27 - Modified: 2026-06-23 - URL: https://gidel.com/application/automation-vision-automatic-test-equipment/ Automation Vision enables modern Automatic Test Equipment (ATE) to test electronic systems and components with high precision. As a result, manufacturers, R&D teams, and maintenance organizations validate devices faster and more consistently. ATE systems perform functional tests, parametric measurements, visual inspection, and reliability tests as part of automated production and validation workflows. Why Automation Vision Matters in ATE Automation Vision improves how ATE systems acquire, analyze, and validate data. Therefore, vision-driven inspection increases accuracy while reducing manual intervention and test variability across complex, high-volume production environments. Operational Demands on Automation Vision Systems To meet production demands, high-performance ATE systems must satisfy strict operational requirements. Consequently, Automation Vision workloads require deterministic behavior and sustained throughput under continuous operation and tight timing constraints. Key Performance Criteria for ATE Vision Test coverage: Executes a wide range of vision-based tests to verify devices meet electrical, functional, and visual specifications. Speed and throughput: High-bandwidth acquisition and real-time processing reduce test cycle time while maintaining result accuracy. Reliability and accuracy: Deterministic system behavior ensures consistent and repeatable results across long production runs. Flexibility and scalability: Adapts to new test requirements, supports multiple device types, and scales with production demand. Real-Time Compression for Automation Vision Pipelines In Automation Vision–based ATE systems, image and data streams can quickly become a throughput bottleneck. To address this, Gidel integrates real-time FPGA-based compression directly into the acquisition pipeline. Gidel’s Compression IPs reduce data bandwidth during capture while preserving test-relevant image fidelity: JPEG Encoder: Standard compression for efficient storage. Lossless Compression: Perfect data preservation for critical analysis. Quality+ Compression: Optimized balance of ratio and fidelity. As a result, ATE systems can sustain higher frame rates, support more cameras in parallel, and stream or store data efficiently without introducing latency or non-deterministic behavior. Because compression runs in hardware on the FPGA, it offloads the CPU and ensures predictable timing. This capability is especially critical in high-volume production testing, long-duration reliability testing, and multi-camera inspection setups where deterministic throughput is mandatory. Boost Your ATE Performance with Automation Vision For this reason, ATE developers rely on Gidel’s expertise in FPGA acceleration to increase system throughput and shorten testing cycles. Gidel’s ready-to-use platforms reduce development effort and accelerate time to market, integrating efficiently into Automation Vision architectures: PCIe Frame Grabbers: High-bandwidth data acquisition for reliable, high-speed automated testing. Mini Jetson Frame Grabbers: Combining Altera FPGA and NVIDIA Jetson for smart ATE systems. Mini Powerful FPGA Modules: Off-the-shelf acceleration for compact, custom test equipment. Customization Tools for ATE Vision Pipelines Furthermore, Gidel’s Software Development Tools and customization services allow developers to tailor imaging and vision pipelines to specific ATE requirements. Consequently, systems achieve deterministic performance, long-term reliability, and scalable test architectures. Need more information? Full Name Email Phone - Published: 2023-03-23 - Modified: 2026-06-23 - URL: https://gidel.com/application/vision-imaging-solutions/ Gidel’s imaging solutions empower companies to deliver high-performance, real-time vision systems. With over 30 years of FPGA expertise, we combine proven experience with innovative technology to provide unmatched flexibility, speed, and scalability. As a result, our solutions help you stay ahead in demanding markets. Why Gidel for Vision & Imaging Solutions? Our modular ecosystem integrates GigE Vision, CoaXPress, and Camera Link frame grabbers, Edge Computers, and FPGA Modules. We also offer advanced Compression options & Image enhancement IPs including HDR and beyond. This unified approach removes bottlenecks, ensures zero frame loss, and keeps CPU usage negligible. Moreover, it frees resources for mission-critical tasks, enabling greater system efficiency. Modular & Future-Proof: Mix and match hardware and IP cores to adapt quickly to changing standards. High Performance: Experience zero frame loss, low latency, and minimal CPU load, even in multi-camera setups. Proven Expertise: Trusted by industries from Industrial Inspection and Medical Imaging to Defense Systems, Broadcast, and Research. Fast Integration: Use advanced tools that simplify setup and reduce risk and time-to-market. AI Vision & Edge Intelligence Modern vision systems increasingly rely on AI to process vast amounts of image data in real time. Gidel’s imaging solutions are purpose-built to support these demanding AI applications. Our FantoVision Edge Computers family combine powerful Altera FPGA-based frame grabbers with integrated NVIDIA Jetson modules, enabling high-speed image acquisition, pre-processing, and AI inference directly at the edge. Seamless AI Integration: Acquire, pre-process, and feed data directly to AI models without overloading the CPU. High-Speed Interfaces: Support for CoaXPress, 10 GigE Vision, and Camera Link ensures compatibility with the most demanding cameras. Real-Time Processing: On-FPGA image enhancement, compression, and multi-camera synchronization enable ultra-low-latency AI workflows. As a result, our solutions empower developers to deploy complex AI-driven vision applications efficiently—from drones and robotics to medical diagnostics and autonomous systems. Development Tools & Expertise Gidel’s advantage goes beyond hardware. Our Software Development Suite supports seamless integration and fast customization. With automated memory management, flexible IP cores, and built-in camera protocol support, engineers can shorten development cycles, enhance system reliability, and adapt quickly to new requirements. Your Competitive Edge in Vision & Imaging Solutions Choosing Gidel means partnering with a proven leader in high-performance vision & imaging solutions. Our technology is designed to meet today’s needs while remaining ready for tomorrow’s demands. With modular hardware, powerful software, and decades of expertise, we help you build reliable, scalable vision systems that keep you ahead of the competition. Need more information? Full Name Email Phone > For additional information, support or sales inquiries, refer to: https://gidel.com/contact-us/ or email sales@gidel.com. (c) 2026 Gidel.