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4 December 2024 Quantitative evaluation and optimization of infrared detection imaging
Wen Sun, Peng Rao, Yejin Li, FengHong Li
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Proceedings Volume 13283, Conference on Spectral Technology and Applications (CSTA 2024); 1328329 (2024) https://doi.org/10.1117/12.3036709
Event: Conference on Spectral Technology and Applications (CSTA 2024), 2024, Dalian, China
Abstract
The performance of infrared imaging systems is influenced by multiple parameters, including optical systems, infrared detectors, and electronic systems, among which the inter-constraint affects resolution, sensitivity, and overall efficiency. To analyze the coupling relationship and evaluate the imaging quality, this study proposes a quantitative evaluation approach based on the entropy-weighted Technique for the Order of Preference by Similarity to the Ideal Solution (TOPSIS) method, focusing on the matched design concerning core system parameters. The validation through space-based image simulation experiments demonstrates consistency between our method and established image quality assessment standards, including the Natural Image Quality Evaluator (NIQE) and the Integrated Local NIQE (IL-NIQE). Optimized via the entropy-weighted approach, the infrared imaging system achieves a significant enhancement in imaging quality, marked by the most considerable improvement in local signal-to-noise ratio (LSNR) by a factor of 1.497, providing technical support for the advancement of in-orbit payloads and holding significant implications for target detection, identification, and tracking.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
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Wen Sun, Peng Rao, Yejin Li, and FengHong Li "Quantitative evaluation and optimization of infrared detection imaging", Proc. SPIE 13283, Conference on Spectral Technology and Applications (CSTA 2024), 1328329 (4 December 2024); https://doi.org/10.1117/12.3036709
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KEYWORDS
Imaging systems
Signal to noise ratio
Infrared imaging
Image quality
Systems modeling
Performance modeling
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