A primal-dual method with linear mapping for a saddle point problem in image deblurring

Journal:JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION

Place of Publication:2016JCR大类-工程技术3区

Key Words:Total variational image deblurring Sub-differential operator Prediction and correction Pairwise primal-dual stepsize

Abstract:In this paper, a simple primal-dual method named PDL is proposed for a convex concave saddle problem and applied to total variational image deblurring. Introduction of linear mapping on proximal term relaxes convergence requirement on pairwise primal-dual stepsize. Simple proof is presented for O(1/N) convergence rate in ergodic sense. Experiments show that performance of PDL is comparable with proximal PDHG (Zhu et al., 2010; Bonettini and Ruggiero, 2012) and PDCP (Chambolle and Pock, 2011) on Gaussian or Salt-Pepper noisy image deblurring.

Note:91 本文去年没有收录序号也没有科研分 2018年考核

Volume:42

Page Number:112-120

Number of Words:15000

Translation or Not:no

First Author:XZP