An Efficient Variational Method for Image Restoration
Joint Authors
Liu, Jun
Lv, Xiao-Guang
Wang, Si
Huang, Ting-Zhu
Source
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-11-28
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
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).
American Psychological Association (APA)
Liu, Jun& Huang, Ting-Zhu& Lv, Xiao-Guang& Wang, Si. 2013. An Efficient Variational Method for Image Restoration. Abstract and Applied Analysis،Vol. 2013, no. 2013, pp.1-11.
https://search.emarefa.net/detail/BIM-455015
Modern Language Association (MLA)
Liu, Jun…[et al.]. An Efficient Variational Method for Image Restoration. Abstract and Applied Analysis No. 2013 (2013), pp.1-11.
https://search.emarefa.net/detail/BIM-455015
American Medical Association (AMA)
Liu, Jun& Huang, Ting-Zhu& Lv, Xiao-Guang& Wang, Si. An Efficient Variational Method for Image Restoration. Abstract and Applied Analysis. 2013. Vol. 2013, no. 2013, pp.1-11.
https://search.emarefa.net/detail/BIM-455015
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-455015