A New Deep Learning-Based Restoration Method for Colour Images

Abstract

As color images have been widely used in many fields, their restoration problem has received wide attention from researchers. This study proposed two solutions for denoising and low illuminance enhancement problems of existing color image restoration methods. At first, this paper built a colour image denoising model of weighted Schatten-p norm based on deep learning, which fully considers differences in the noise level of each channel of colour images, and could give a better denoising effect. Then, this study proposed a low illuminance color image enhancement algorithm that combines Gamma transform and Contrast Limited Adaptive Histogram Equalization (CLAHE), which could better balance image contrast enhancement and noise suppression. Studies of these two parts have both gained good results in terms of theory and experiment, and they could push the progress of colour image restoration technology and provide valuable references for related fields.