Alternating split Bregman method for the bilaterally constrained image deblurring problem

Baoli Shi, Zhi-Feng Pang and Jun Wu

Applied Mathematics and Computation, 2015, vol. 250, issue C, 402-414

Abstract: This paper studies the image deblurring problem based on a bilateral constraint by convexly combining two classes of total-variation-type functionals. The proposed model including two L1-norm terms leads to some numerical difficulties, so we employ the alternating split Bregman method (ASB) to solve it which can be reinterpreted as Douglas–Rachford splitting applied to the dual problem. We also prove that the alternating split Bregman method owns the convergence rate O1M for the iteration M. Experimental results demonstrate the viability and efficiency of the proposed model and algorithm to restore blurring and noisy images.

Keywords: Image deblurring; Bilateral constraint; ROF model; High-order model; Alternating split Bregman method (search for similar items in EconPapers)
Date: 2015
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0096300314015094
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:apmaco:v:250:y:2015:i:c:p:402-414

DOI: 10.1016/j.amc.2014.11.004

Access Statistics for this article

Applied Mathematics and Computation is currently edited by Theodore Simos

More articles in Applied Mathematics and Computation from Elsevier
Bibliographic data for series maintained by Catherine Liu ().