Some First-Order Algorithms for Total Variation Based Image Restoration

Authors:
Jean-François Aujol
Affiliations:
CMLA, ENS Cachan, CNRS, UniverSud, Cachan, France
Venue:
Journal of Mathematical Imaging and Vision
Year:
2009

Citing 25
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Abstract

This paper deals with first-order numerical schemes for image restoration. These schemes rely on a duality-based algorithm proposed in 1979 by Bermùdez and Moreno. This is an old and forgotten algorithm that is revealed wider than recent schemes (such as the Chambolle projection algorithm) and able to improve contemporary schemes. 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. We make some comparisons with a class of efficient algorithms (proved to be optimal among first-order numerical schemes) recently introduced by Y. Nesterov.