Corrected rank residual constraint model for image denoising

In this paper, a novel image denoising model is proposed, named Corrected Rank Residual Constraint (CRRC). To overcome the drawback that L1 norm penalty yields biased estimators and cannot achieve best estimation performance, proposed CRRC incorporates adaptive correction term with minimization to improve sparsity of data fidelity enforced on rank residual. The existence uniqueness solutions are also studied, optimization method for solving given. studies show can not only residual but over-shrinkage large singular values. Experimental results demonstrate outperforms many state-of-the-art methods in both objective perceptual quality.