These notes describe the derivation of a simple algorithm for signal denoising (filtering) based on total variation (TV). Total variation based filtering was introduced by Rudin, Osher, and Fatemi [8]. TV denoising is an effective filtering method for recovering piecewise-constant signals. Many algorithms have been proposed to implement total variation filtering. The one described in these notes is by Chambolle [3]. (Note: Chambolle described another algorithm in [2]). Although the algorithm can be derived in several different ways, the derivation presented here is based on descriptions given in [1, 10]. The derivation is based on the min-max property and the majorization-minimization procedure. Total variation is often used for image filtering and restoration, however, to simplify the presentation of the TV filtering algorithm these notes concentrate on one-dimensional signal filtering only. In addition, the algorithm described here may converge slowly for some problems. Faster algorithms for TV filtering have recently been developed, for example [1,10]. The development of fast, robust algorithms for TV and related non-linear filtering is an active topic of research.
[1]
Robert D. Nowak,et al.
Majorization–Minimization Algorithms for Wavelet-Based Image Restoration
,
2007,
IEEE Transactions on Image Processing.
[2]
Antonin Chambolle,et al.
Total Variation Minimization and a Class of Binary MRF Models
,
2005,
EMMCVPR.
[3]
Mário A. T. Figueiredo,et al.
Signal restoration with overcomplete wavelet transforms: comparison of analysis and synthesis priors
,
2009,
Optical Engineering + Applications.
[4]
J. Hiriart-Urruty,et al.
Convex analysis and minimization algorithms
,
1993
.
[5]
Stephen J. Wright,et al.
Duality-based algorithms for total-variation-regularized image restoration
,
2010,
Comput. Optim. Appl..
[6]
L. Rudin,et al.
Nonlinear total variation based noise removal algorithms
,
1992
.
[7]
Marc Teboulle,et al.
Fast Gradient-Based Algorithms for Constrained Total Variation Image Denoising and Deblurring Problems
,
2009,
IEEE Transactions on Image Processing.
[8]
M. Nikolova.
An Algorithm for Total Variation Minimization and Applications
,
2004
.
[9]
丸山 徹.
Convex Analysisの二,三の進展について
,
1977
.