The method we present in this paper has been motivated by a restoration problem in a tomography context. We are interested in blurred and noised binary images restoration. We consider the discrete version of a minimization problem settled in the space of bounded variation functions. We give a general abstract formulation of the (discrete) optimization problem with binary constraints and provide approximate and penalized formulations. Convergence results are given and we present numerical tests.

Contact details are reproduced from the original publication and may be historical.

Maïtine Bergounioux

UFR Sciences - Mathématiques, Université d'Orléans, Route de Chartres, 45067 Orléans, France
and: Labo. MAPMO, UMR 6628

maitine.bergounioux@univ-orleans.fr

Mounir Haddou

UFR Sciences - Mathématiques, Université d'Orléans, Route de Chartres, 45067 Orléans, France
and: Labo. MAPMO, UMR 6628

mounir@haddou@univ-orleans.fr

M. Bergounioux, M. Haddou. “A New Relaxation Method for a Discrete Image Restoration Problem.” Journal of Convex Analysis 17 (2010), No. 3&4, 861–883. https://doi.org/10.68381/jca17055