Some first-order algorithms for total variation based image restoration - Archive ouverte HAL Access content directly
Journal Articles Journal of Mathematical Imaging and Vision Year : 2009

Some first-order algorithms for total variation based image restoration

Abstract

This paper deals with numerical schemes for image restoration. These schemes rely on a duality-based algorithm proposed in 1979 by Bermudez and Moreno, and on general minimization schemes recently developped by Y. Nesterov. Total variation regularization and smoothed total variation regularization are investigated. Algorithms are presented for such regularizations in image restoration. We prove the convergence of all the proposed schemes. We illustrate our study with numerous numerical examples, and we make comparisons between the different schemes presented in the paper. Our experiments are in favor of Bermudez-Moreno approach to get a fast approximation for smoothed total variation regularization, whereas Y. Nesterov.
Fichier principal
Vignette du fichier
aujol_algo_final.pdf (544.94 Ko) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

hal-00260494 , version 1 (04-03-2008)
hal-00260494 , version 2 (12-09-2009)

Identifiers

Cite

Jean-François Aujol. Some first-order algorithms for total variation based image restoration. Journal of Mathematical Imaging and Vision, 2009, 34 (3), pp.307-327. ⟨10.1007/s10851-009-0149-y⟩. ⟨hal-00260494v2⟩
313 View
896 Download

Altmetric

Share

Gmail Facebook X LinkedIn More