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EO system design and performance optimization by image-based end-to-end modeling

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Author: Bijl, P. · Hogervorst, M.A.
Source:Krapels, G.C.Holst, K.A., Proceedings of SPIE - The International Society for Optical Engineering, Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XXX 2019, 16 April 2019 through 18 April 2019
Identifier: 869402
doi: doi:10.1117/12.2519946
Article number: 110010G
Keywords: EO · IR · TOD · Cameras · CMOS integrated circuits · Economic and social effects · Imaging systems · Iridium · Optical data processing · Optical systems · Signal to noise ratio · Thermography (imaging) · ECOMOS · EOSTAR · Sensor model · Sensor tests · Target acquisition · Integrated circuit design


Image-based Electro-Optical system simulation including an end-to-end performance test is a powerful tool to characterize a camera system before it has been built. In particular, it can be used in the design phase to make an optimal trade-off between performance on the one hand and SWaPC (Size, Weight, Power and Cost) criteria on the other. During the design process, all components can be simulated in detail, including optics, sensor array properties, chromatic and geometrical lens corrections, signal processing, and compression. Finally, the overall effect on the outcome can be visualized, evaluated and optimized. In this study, we developed a detailed model of the CMOS camera system imaging chain (including scene, image processing and display). In parallel a laboratory sensor test, analytical model predictions and an image-based simulation were applied to two operational high-end CMOS camera lens assemblies (CLA) with different FPA sizes (2.5K and 4K) and optics. The model simulation was evaluated by comparing simulated (display) stills and videos with recorded imagery using both physical (SNR) and psychophysical measures (acuity and contrast thresholds using the TOD-methodology) at different shutter times, zoom settings, target sizes and contrasts, target positions in the visual field, and target speeds. The first results show the model simulations are largely in line with the recorded sensor images with some minor deviations. The final goal of the study is a detailed, validated and powerful sensor performance prediction model. © 2019 SPIE. Downloading of the abstract is permitted for personal use only.