Open Access
2013 An Efficient Variational Method for Image Restoration
Jun Liu, Ting-Zhu Huang, Xiao-Guang Lv, Si Wang
Abstr. Appl. Anal. 2013(SI31): 1-11 (2013). DOI: 10.1155/2013/213536


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).


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Jun Liu. Ting-Zhu Huang. Xiao-Guang Lv. Si Wang. "An Efficient Variational Method for Image Restoration." Abstr. Appl. Anal. 2013 (SI31) 1 - 11, 2013.


Published: 2013
First available in Project Euclid: 26 February 2014

zbMATH: 1319.94017
MathSciNet: MR3134164
Digital Object Identifier: 10.1155/2013/213536

Rights: Copyright © 2013 Hindawi

Vol.2013 • No. SI31 • 2013
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