Quantitative evaluation and optimization of infrared detection imaging

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.