An Inexact Double Primal-Dual Algorithm for Saddle Point Problems. Issue 1 (April 2021) - Fang, Changjie; Chen, Jingyu
Abstract: In this paper, we study a saddle point problem and propose an inexact double primal-dual algorithm for solving the saddle point problem. The sequence generated by the proposed algorithm is proved to globally converge to the saddle point of the saddle point problem in the ergodic sense, and the convergence rate of the algorithm is also obtained. For the model of total variation image processing, the performance of the algorithm is demonstrated. Simulation results show that our method is more efficient in image denoising compared with existing methods.