An inexact primal-dual method with correction step for a saddle point problem in image debluring

Fuente: arXiv
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Main Authors: Fang, Changjie, Hu, Liliang, Chen, Shenglan
Format: Preprint
Published: 2021
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author Fang, Changjie
Hu, Liliang
Chen, Shenglan
author_facet Fang, Changjie
Hu, Liliang
Chen, Shenglan
contents In this paper,we present an inexact primal-dual method with correction step for a saddle point problem by introducing the notations of inexact extended proximal operators with symmetric positive definite matrix $D$. Relaxing requirement on primal-dual step sizes, we prove the convergence of the proposed method. We also establish the $O(1/N)$ convergence rate of our method in the ergodic sense. Moreover, we apply our method to solve TV-L$_1$ image deblurring problems. Numerical simulation results illustrate the efficiency of our method.
format Preprint
id arxiv_https___arxiv_org_abs_2112_00389
institution arXiv
publishDate 2021
record_format arxiv
spellingShingle An inexact primal-dual method with correction step for a saddle point problem in image debluring
Fang, Changjie
Hu, Liliang
Chen, Shenglan
Optimization and Control
In this paper,we present an inexact primal-dual method with correction step for a saddle point problem by introducing the notations of inexact extended proximal operators with symmetric positive definite matrix $D$. Relaxing requirement on primal-dual step sizes, we prove the convergence of the proposed method. We also establish the $O(1/N)$ convergence rate of our method in the ergodic sense. Moreover, we apply our method to solve TV-L$_1$ image deblurring problems. Numerical simulation results illustrate the efficiency of our method.
title An inexact primal-dual method with correction step for a saddle point problem in image debluring
topic Optimization and Control
url https://arxiv.org/abs/2112.00389