  Group sparse representation has shown promising results in image debulrring
and image inpainting in GSR [3] , the main reason that lead to the success is
by exploiting Sparsity and Nonlocal self-similarity (NSS) between patches on
natural images, and solve a regularized optimization problem. However, directly
adapting GSR[3] in image denoising yield very unstable and non-satisfactory
results, to overcome these issues, this paper proposes a progressive image
denoising algorithm that successfully adapt GSR [3] model and experiments shows
the superior performance than some of the state-of-the-art methods.
