@inproceedings{99028057ba774013bf7b0271363d5cbf,
title = "On total variation denoising: A new majorization-minimization algorithm and an experimental comparison with wavalet denoising",
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.",
keywords = "Image denoising, Image restoration, Majorization-minimization algorithms, Total variation",
author = "Figueiredo, {M. A.T.} and Dias, {J. B.} and Oliveira, {J. P.} and Nowak, {R. D.}",
year = "2006",
doi = "10.1109/ICIP.2006.313050",
language = "British English",
isbn = "1424404819",
series = "Proceedings - International Conference on Image Processing, ICIP",
pages = "2633--2636",
booktitle = "2006 IEEE International Conference on Image Processing, ICIP 2006 - Proceedings",
note = "2006 IEEE International Conference on Image Processing, ICIP 2006 ; Conference date: 08-10-2006 Through 11-10-2006",
}