Paper Info
Title
On Total Variation Denoising: A New Majorization-Minimization Algorithm and an Experimental Comparisonwith Wavalet Denoising
Abstract
ABSTRACT Image denoising is a classical problem which has been addressed using a variety of conceptual frameworks,and computational,tools. Most approaches use some form of penalty/prior as a regularizer, expressing a preference for images with some,form of (generalized) “smoothness”. Total variation (TV) and wavelet-based methods have received a great deal of attention in the last decade and are among the state of the art in this problem. However, as far as we know, no experimental studies have been carried out, comparing the relative performance,of the two classes of methods. In this paper, we present the results of such a comparison. Prior to that, we introduce a new majorization-minimization algorithm to implement the TV denoising criterion. We conclude that TV is outperformed by recent state of the art wavelet-based denoising methods, but performs competitively with older wavelet-based methods. Index terms ‐ Image restoration, total variation, image denoising, majorization-minimization algorithms.
Year
DOI
Venue
2006
10.1109/ICIP.2006.313050
Atlanta, GA
Keywords
Field
DocType
image denoising,wavelet transforms,image denoising,majorization-minimization algorithm,total variation method,wavelet-based method,Image restoration,image denoising,majorization-minimization algorithms,total variation
Noise reduction,Pattern recognition,Basis pursuit denoising,Non-local means,Computer science,Algorithm,Total variation denoising,Artificial intelligence,Image restoration,Video denoising,Wavelet transform,Wavelet
Conference
ISSN
ISBN
Citations 
1522-4880
1-4244-0480-0
37
PageRank 
References 
Authors
3.25
7
4
Name
Order
Citations
PageRank
Mário A. T. Figueiredo17203561.50
José M. Bioucas-dias2373.25
João P. Oliveira3374.60
Robert D. Nowak4373.25