An Efficient Total Variation Minimization Method for Image Restoration

被引：19

作者：

Cong Thang Pham ^{[1
]}

Thi Thu Thao Tran ^{[2
]}

Gamard, Guilhem ^{[3
]}

机构：

[1] Univ Danang Univ Sci & Technol, 54 Nguyen Luong Bang, Danang, Vietnam

[2] Univ Danang Univ Econ, 71 Ngu Hanh Son, Danang, Vietnam

[3] ENS Lyon, LIP, 46 Allee Italie, F-69364 Lyon, France

来源：

INFORMATICA | 2020年 / 31卷 / 03期

关键词：

total variation; image restoration; mixed Poisson-Gaussian noise; convex optimization; split-Bregman method; RESTORING BLURRED IMAGES; POISSON; NOISE; ALGORITHM;

D O I：

10.15388/20-INFOR407

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper, we present an effective algorithm for solving the Poisson-Gaussian total variation model. The existence and uniqueness of solution for the mixed Poisson-Gaussian model are proved. Due to the strict convexity of the model, the split-Bregman method is employed to solve the minimization problem. Experimental results show the effectiveness of the proposed method for mixed Poisson-Gaussion noise removal. Comparison with other existing and well-known methods is provided as well.

引用

页码：539 / 560

页数：22

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