An enhanced image denoising method using method noise

Method noise which is the difference between a noisy image and its denoised version, often contains image structure and detail information due to imperfect denoising. This paper analyzes the method noise and establishes a model to extract image information submerged in the method noise. Then the extracted image information is fed back to the denoised image to conduct the next denoising step. The whole denoising scheme is an iterative process. Each iteration is implemented in two stages: the first stage is to use the method of weighted nuclear norm minimization (WNNM) to process a noisy image, and the second stage is to extract the useful image information using Gaussian filter and feed it back. Experimental results show that the proposed method is superior to other state-of-the-art methods in terms of objective and subjective quality performance.