Low light image enhancement method based on guided filtering

Bin Yao; Zhen Han; Shiying Kang; Xuanying Wei; Lifeng He; Pengtao Shi

doi:10.1117/12.2615625

11 November 2021 Low light image enhancement method based on guided filtering

Bin Yao, Zhen Han, Shiying Kang, Xuanying Wei, Lifeng He, Pengtao Shi

Proceedings Volume 12076, 2021 International Conference on Image, Video Processing, and Artificial Intelligence; 120760I (2021) https://doi.org/10.1117/12.2615625
Event: Fourth International Conference on Image, Video Processing, and Artificial Intelligence (IVPAI 2021), 2021, Shanghai, China

Abstract

Low light image enhancement methods based on classic Retinex model attempts to estimate the illumination component and to project it back to the corresponding reflectance. Therefore, the accuracy of illumination component estimated determines the performance of enhancement results. Based on Retinex model, this paper proposed an illumination component estimating method by guided filtering. In the proposed method, bright channel is used for obtaining a rough illumination map. Then, the gray image converted by the input low light image is employed as the guidance image and we refine the rough illumination map for obtaining a structural-awared illumination map by guided filtering. Lastly, the enhanced image can be achieved by a simple computation. Experimental results demonstrated that the performance of the proposed method significantly overpasses conventional low light image enhancement methods.

Citation Download Citation

Bin Yao, Zhen Han, Shiying Kang, Xuanying Wei, Lifeng He, and Pengtao Shi "Low light image enhancement method based on guided filtering", Proc. SPIE 12076, 2021 International Conference on Image, Video Processing, and Artificial Intelligence, 120760I (11 November 2021); https://doi.org/10.1117/12.2615625

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