An Efficient Variational Method for Image Restoration. (28th November 2013)

• Record Type: Journal Article
• Authors: Liu, Jun; Huang, Ting-Zhu; Lv, Xiao-Guang; Wang, Si
• Other Names: Shi Peilin Academic Editor.
• Is Part Of: Abstract and applied analysis. Volume 2013(2013)
• Publication Date: 2013-11-28
• Subjects: Mathematical analysis -- Periodicals; Mathematical analysis; Applied Mathematics; Mathematical Analysis; Periodicals; 515.05
• DOI: 10.1155/2013/213536
• Languages: English
• ISSNs: 1085-3375

Abstract

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).