Document Type
Journal Article
Department/Unit
Department of Mathematics
Title
Fast minimization methods for solving constrained total-variation superresolution image reconstruction
Language
English
Abstract
In this paper, we study the problem of reconstructing a high-resolution image from several decimated, blurred and noisy low-resolution versions of the high-resolution image. The problem can be formulated as a combination of the total variation (TV) inpainting model and the superresolution image reconstruction model. The main purpose of this paper is to develop an inexact alternating direction method for solving such constrained TV image reconstruction problem. Experimental results are given to show that the proposed algorithm is effective and efficient. © 2010 Springer Science+Business Media, LLC.
Keywords
Alternating direction methods, Constrained total-variation, Inexact computation, Superresolution image reconstruction
Publication Date
2011
Source Publication Title
Multidimensional Systems and Signal Processing
Volume
22
Issue
3-1
Start Page
259
End Page
286
Publisher
Springer Verlag
DOI
10.1007/s11045-010-0137-9
Link to Publisher's Edition
http://dx.doi.org/10.1007/s11045-010-0137-9
ISSN (print)
09236082
ISSN (electronic)
15730824
APA Citation
Ng, M., Wang, F., & Yuan, X. (2011). Fast minimization methods for solving constrained total-variation superresolution image reconstruction. Multidimensional Systems and Signal Processing, 22 (3-1), 259-286. https://doi.org/10.1007/s11045-010-0137-9