Group sparsity has shown great potential in various low-level vision tasks(e.g, image denoising, deblurring and inpainting). In this paper, we propose anew prior model for image denoising via group sparsity residual constraint(GSRC). To enhance the performance of group sparse-based image denoising, theconcept of group sparsity residual is proposed, and thus, the problem of imagedenoising is translated into one that reduces the group sparsity residual. Toreduce the residual, we first obtain some good estimation of the group sparsecoefficients of the original image by the first-pass estimation of noisy image,and then centralize the group sparse coefficients of noisy image to theestimation. Experimental results have demonstrated that the proposed method notonly outperforms many state-of-the-art denoising methods such as BM3D and WNNM,but results in a faster speed.
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