Mixed overlapping group sparse and nonconvex fractional-order image restoration algorithm

A nonconvex total variation image denoising model with a double regularization penalty term is proposed in this paper, which effectively overcomes the shortcomings of a single regularization penalty term. The Chambolle-Pock primal-dual algorithm framework is used to solve the model, and the optimal approximate solution is obtained. This is also a new application of the primal-dual algorithm for solving nonconvex problems. Simulation experiments show the effectiveness and feasibility of the proposed algorithm compared with several existing methods, and its convergence is also verified experimentally.