The goal of the article is to provide a methodology of improving images quality in low-light conditions trough fusion of data received from telecamera and thermal camera. Data from thermal camera uses for compensation of significant illumination reduction in poor lighting conditions and allow keep required level of information. Proposed method establishes dynamic regulation of fusion coefficients depending on brightness level to minimize artifacts, increase edge sharpness, and improve object detectability. Developed model enables investigation of the influence of algorithmic parameters on key quality indicators, particularly PSNR, SSIM and target detection metrics. It has been shown that implementation of adaptive multimodal fusion principles ensures an increase in structural similarity by 15-20% and improvement in target detection accuracy in dark scenes by over 25% compared to using individual channels.
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