Group Sparse Coding for Image Denoising

LUOYU CHEN, Fei Wu

Abstract:

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.