Proximal ADMM Approach for Image Restoration with Mixed Poisson-Gaussian Noise (Journal of Computational Mathematics, 2024)
Image restoration based on total variation has been widely studied owing to its edge-preservation properties. In this study, we consider the total variation infimal convolution(TV-IC) image restoration model for eliminating mixed Poisson-Gaussian noise. Based onthe alternating direction method of multipliers (ADMM), we propose a complete splittingproximal bilinear constraint ADMM algorithm to solve the TV-IC model. We prove theconvergence of the proposed algorithm under mild conditions. In contrast with otheralgorithms used for solving the TV-IC model, the proposed algorithm does not involveany inner iterations, and each subproblem has a closed-form solution. Finally, numericalexperimental results demonstrate the efficiency and effectiveness of the proposed algorithm.
Keywords: Image restoration; Mixed Poisson-Gaussian noise; Alternating direction method of multipliers; Total variation.