A New Low-Light Image Enhancement Algorithm Using Camera Response Model

Zhenqiang Ying, Ge Li, Yurui Ren, Ronggang Wang, Wenmin Wang; Proceedings of the IEEE International Conference on Computer Vision (ICCV), 2017, pp. 3015-3022

Low-light images are not conducive to human observation and computer vision algorithms due to their low visibility. To solve this problem, many image enhancement techniques have been proposed. However, existing techniques inevitably introduce color and lightness distortion when increasing visibility. To lower the distortion, we propose a novel enhancement method using the response characteristics of cameras. First, we investigate the relationship between two images with different exposures to obtain an accurate camera response model. Then we borrow the illumination estimation techniques to estimate the exposure ratio map. Finally, we use our camera response model to adjust each pixel to its desired exposure according to the estimated exposure ratio map. Experiments show that our method can obtain enhancement results with less color and lightness distortion compared to several state-of-the-art methods.