## Abstract and Applied Analysis

### An Efficient Variational Method for Image Restoration

#### Abstract

Image restoration is one of the most fundamental issues in imaging science. Total variation regularization is widely used in image restoration problems for its capability to preserve edges. In this paper, we consider a constrained minimization problem with double total variation regularization terms. To solve this problem, we employ the split Bregman iteration method and the Chambolle’s algorithm. The convergence property of the algorithm is established. The numerical results demonstrate the effectiveness of the proposed method in terms of peak signal-to-noise ratio (PSNR) and the structure similarity index (SSIM).

#### Article information

Source
Abstr. Appl. Anal., Volume 2013, Special Issue (2013), Article ID 213536, 11 pages.

Dates
First available in Project Euclid: 26 February 2014

https://projecteuclid.org/euclid.aaa/1393447480

Digital Object Identifier
doi:10.1155/2013/213536

Mathematical Reviews number (MathSciNet)
MR3134164

Zentralblatt MATH identifier
1319.94017

#### Citation

Liu, Jun; Huang, Ting-Zhu; Lv, Xiao-Guang; Wang, Si. An Efficient Variational Method for Image Restoration. Abstr. Appl. Anal. 2013, Special Issue (2013), Article ID 213536, 11 pages. doi:10.1155/2013/213536. https://projecteuclid.org/euclid.aaa/1393447480

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