FIXED-POINT-LIKE METHOD FOR A NEW TOTAL VARIATION-BASED IMAGE RESTORATION MODEL

被引：0

作者：

Won, Yu Jin ^{[1
]}

Yun, Jae Heon ^{[1
]}

机构：

[1] Chungbuk Natl Univ, Coll Nat Sci, Dept Math, Cheongju 28644, South Korea

来源：

JOURNAL OF APPLIED MATHEMATICS & INFORMATICS | 2020年 / 38卷 / 5-6期

基金：

新加坡国家研究基金会;

关键词：

Image restoration; Total variation; Fixed-point method; Split Bregman method; Proximity operator;

D O I：

10.14317/jami.2020.519

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

In this paper, we first propose a new total variation-based regularization model for image restoration. We next propose a fixed-point-like method for solving the new image restoration model, and then we provide convergence analysis for the fixed-point-like method. To evaluate the feasibility and efficiency of the fixed-point-like method for the new proposed total variation-based regularization model, we provide numerical experiments for several test problems.

引用

页码：519 / 532

页数：14

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