Journal of Applied Mathematics

Split Bregman Iteration Algorithm for Image Deblurring Using Fourth-Order Total Bounded Variation Regularization Model

Yi Xu, Ting-Zhu Huang, Jun Liu, and Xiao-Guang Lv

Full-text: Open access

Abstract

We propose a fourth-order total bounded variation regularization model which could reduce undesirable effects effectively. Based on this model, we introduce an improved split Bregman iteration algorithm to obtain the optimum solution. The convergence property of our algorithm is provided. Numerical experiments show the more excellent visual quality of the proposed model compared with the second-order total bounded variation model which is proposed by Liu and Huang (2010).

Article information

Source
J. Appl. Math., Volume 2013 (2013), Article ID 238561, 11 pages.

Dates
First available in Project Euclid: 14 March 2014

Permanent link to this document
https://projecteuclid.org/euclid.jam/1394807955

Digital Object Identifier
doi:10.1155/2013/238561

Mathematical Reviews number (MathSciNet)
MR3049429

Zentralblatt MATH identifier
1266.65040

Citation

Xu, Yi; Huang, Ting-Zhu; Liu, Jun; Lv, Xiao-Guang. Split Bregman Iteration Algorithm for Image Deblurring Using Fourth-Order Total Bounded Variation Regularization Model. J. Appl. Math. 2013 (2013), Article ID 238561, 11 pages. doi:10.1155/2013/238561. https://projecteuclid.org/euclid.jam/1394807955


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