PAPADAKIS, Nicolas; YILDIZOGLU, Romain; AUJOL, Jean-François; CASELLES, Vicent

doi:10.1137/120900307

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PAPADAKIS, Nicolas
Modelling, Observations, Identification for Environmental Sciences [MOISE]
Institut de Mathématiques de Bordeaux [IMB]

YILDIZOGLU, Romain
Institut de Mathématiques de Bordeaux [IMB]

AUJOL, Jean-François
Institut de Mathématiques de Bordeaux [IMB]

Langue

Article de revue

Ce document a été publié dans

SIAM Journal on Imaging Sciences. 2013-12-02, vol. 6, n° 4, p. 2603-2639

Society for Industrial and Applied Mathematics

Résumé en anglais

This paper is concerned with the problem of relaxing non convex functionals, used in image processing, into convex problems. We review most of the recently introduced relaxation methods, and we propose a new convex one based on a probabilistic approach, which has the advantages of being intuitive, flexible and involving an algorithm without inner loops. We investigate in detail the connections between the solutions of the relaxed functionals with a minimizer of the original one. Such connection is demonstrated only for non convex relaxation which turns out to be quite robust to initialization. As a case of study, we illustrate our theoretical analysis with numerical experiments, namely for the optical flow problem.< Réduire

Mots clés en anglais

multilabel problems

convex relaxation

segmentation

disparity and optical flow

URI

https://oskar-bordeaux.fr/handle/20.500.12278/189636

DOI

http://dx.doi.org/10.1137/120900307

Project ANR

Adaptivité pour la représentation des images naturelles et des textures - ANR-08-EMER-0009

Origine

Importé de hal

Unités de recherche

Institut de Mathématiques de Bordeaux (IMB) - UMR 5251