Paper
9 October 2018 Image-based end-to-end EO system performance modeling as a design and optimization tool
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Abstract
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 can be optimized. In this study, we developed a detailed model of the CMOS camera system imaging chain (including scene, image processing and display). The model simulation was evaluated by comparing simulated (display) imagery with recorded image using both physical (SNR) and psychophysical measures (acuity and contrast thresholds using the TOD-methodology with a human observer) for a range of conditions: different light levels, moving stimuli with different speeds, movies and single frames. The performance analysis show that the model simulations are largely in line with the recorded sensor images with some minor deviations. The result of the study is a detailed, validated and powerful sensor performance prediction model. This project has received funding from the Electronic Component Systems for European Leadership Joint Undertaking.
© (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
M. A. Hogervorst, P. Bijl, P. Fuller, R. Aartsen, and L. Jovanov "Image-based end-to-end EO system performance modeling as a design and optimization tool", Proc. SPIE 10795, Electro-Optical and Infrared Systems: Technology and Applications XV, 107950O (9 October 2018); https://doi.org/10.1117/12.2326284
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Cited by 1 scholarly publication.
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KEYWORDS
Sensors

Signal to noise ratio

Image sensors

Electro optical modeling

Systems modeling

Imaging systems

Image processing

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