Research on related algorithms of low illumination image enhancement

Xue Gao; Yimin Tian; Fangfang Song; Shuai Yang; Meijun Zheng; Qingxin Yang

doi:10.1117/12.2631153

18 March 2022 Research on related algorithms of low illumination image enhancement

Xue Gao, Yimin Tian, Fangfang Song, Shuai Yang, Meijun Zheng, Qingxin Yang

Proceedings Volume 12168, International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2021); 121682D (2022) https://doi.org/10.1117/12.2631153
Event: International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2021), 2021, Harbin, China

Abstract

Due to the lack of illumination, uneven lighting, weather change, relative motion, overexposure and other complex natural environmental factors, the camera can not always capture high visibility images, which brings great challenges to the later application of machine vision. Therefore, it is necessary and imperative to post process the image to make it still have high-quality standards in a polymorphic environment. Low illumination color images not only have the characteristics of low brightness, but also are accompanied by noise and color offset due to equipment accuracy. In addition, it is easy to amplify noise, color offset, halo artifacts, unnatural gradient order and so on. For low illumination image, how to deal with its related problems, this paper introduces histogram equalization algorithm and Retinex algorithm.

Citation Download Citation

Xue Gao, Yimin Tian, Fangfang Song, Shuai Yang, Meijun Zheng, and Qingxin Yang "Research on related algorithms of low illumination image enhancement", Proc. SPIE 12168, International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2021), 121682D (18 March 2022); https://doi.org/10.1117/12.2631153

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