LECARM: Low-Light Image Enhancement Using the Camera Response Model 论文

摘要

Low-light image enhancement algorithms can improve the visual quality of low-light images and support the extraction of valuable information for some computer vision techniques. However, existing techniques inevitably introduce color and lightness distortions when enhancing the images. To lower the distortions, we propose a novel enhancement framework using the response characteristics of cameras. First, we discuss how to determine a reasonable camera response model and its parameters. Then, we use the illumination estimation techniques to estimate the exposure ratio for each pixel. Finally, the selected camera response model is used to adjust each pixel to the desired exposure according to the estimated exposure ratio map. Experiments show that our method can obtain enhancement results with fewer color and lightness distortions compared with the several state-of-the-art methods.