An adaptive primal-dual image denoising algorithm

A primal-dual model for image denoising is proposed based on duality principle. We theoretically analyze its equivalency with the ROF variation model, and its structural similarity with the saddle-point optimization model. The primal-dual algorithm based on resolvent is used for solving the model. In terms of parameter selection, the regularization parameter is updated adaptively based on the discrepancy principle. The experiment results show that the proposed primal-dual denoising algorithm is effective in improving the visual effect.