Due to the ill-posed nature of image denoising problem, good image priors are of great
importance for an effective restoration. Nonlocal self-similarity and sparsity are two popular
and widely used image priors which have led to several state-of-the-art methods in natural
image denoising. In this paper, we take advantage of these priors and propose a new
denoising algorithm based on sparse and low-rank representation of image patches under a
nonlocal framework. This framework consists of two complementary steps. In the first step …