An algorithm for image restoration with mixed noise using total variation regularization

被引：8

作者：

Cong Thang Pham ^{[1
,2
]}

Gamard, Guilhem ^{[1
]}

Kopylov, Andrei ^{[3
]}

Thi Thu Thao Tran ^{[3
,4
]}

机构：

[1] Natl Res Univ Higher Sch Econ, Fac Comp Sci, Moscow, Russia

[2] Univ Sci & Technol, Univ Da Nang, Da Nang, Vietnam

[3] Tula State Univ, Inst Appl Math & Comp Sci, Tula, Russia

[4] Univ Econ, Univ Da Nang, Da Nang, Vietnam

来源：

TURKISH JOURNAL OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCES | 2018年 / 26卷 / 06期

关键词：

Image denoising; Gaussian noise; Poisson noise; total variation regularization; mixed noise distribution; gradient flow; EM APPROACH; MODEL;

D O I：

10.3906/elk-1803-100

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

We present here an effective scheme for image denoising based on total variation regularization. The proposed scheme allows to efficiently remove Poisson noise as well as Gaussian noise simultaneously with the help of a new kind of data fidelity term, suitable for the mixed Poisson-Gaussian noise model. The results show that the algorithm corresponding to our new scheme outperforms the existing methods for mixed Poisson-Gaussian noise removal.

引用

页码：2831 / +

页数：20

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