Geodesic
A New Relaxation Method for a Discrete Image Restoration Problem
Journal of convex analysis, Tome 17 (2010) no. 3, pp. 861-883
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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.
Mots-clés : Tomography, optimization, penalization 
@article{JCA_2010_17_3_JCA_2010_17_3_a9,
     author = {M. Bergounioux and M. Haddou},
     title = {A {New} {Relaxation} {Method} for a {Discrete} {Image} {Restoration} {Problem}},
     journal = {Journal of convex analysis},
     pages = {861--883},
     year = {2010},
     volume = {17},
     number = {3},
     url = {http://geodesic.mathdoc.fr/item/JCA_2010_17_3_JCA_2010_17_3_a9/}
}
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M. Bergounioux; M. Haddou. A New Relaxation Method for a Discrete Image Restoration Problem. Journal of convex analysis, Tome 17 (2010) no. 3, pp. 861-883. http://geodesic.mathdoc.fr/item/JCA_2010_17_3_JCA_2010_17_3_a9/