A parallel proximal splitting method for disparity estimation from multicomponent images under illumination variation

Caroline Chaux 1 Mireille El Gheche 1 Joumana Farah 2 Jean-Christophe Pesquet 1 Beatrice Pesquet-Popescu 3
1 LIGM - Laboratoire d'Informatique Gaspard-Monge
2 Department of Telecommunications, Faculty of Engineering
3 LTCI - Laboratoire Traitement et Communication de l'Information
Abstract : Proximal splitting algorithms play a central role in finding the numerical solution of convex optimization problems. This paper addresses the problem of stereo matching of multi-component images by jointly estimating the disparity and the illumination variation. The global formulation being non-convex, the problem is addressed by solving a sequence of convex relaxations. Each convex relaxation is non trivial and involves many constraints aiming at imposing some reg- ularity on the solution. Experiments demonstrate that the method is efficient and provides better results compared with other approaches.
Document type :
Journal articles
Complete list of metadatas

Cited literature [41 references]  Display  Hide  Download
https://hal-upec-upem.archives-ouvertes.fr/hal-00733454
Contributor : Mireille El Gheche <>
Submitted on : Wednesday, September 19, 2012 - 11:04:15 AM
Last modification on : Thursday, October 17, 2019 - 12:36:06 PM
Long-term archiving on: Thursday, December 20, 2012 - 3:45:24 AM

File

2011_jmiv_hal.pdf
Files produced by the author(s)

Identifiers

Collections

CNRS | ENPC | LIGM_SIGNAL | LIGM | PARISTECH | INSTITUT-TELECOM | UNIV-MLV | UPEC-UPEM | LTCI

Citation

Caroline Chaux, Mireille El Gheche, Joumana Farah, Jean-Christophe Pesquet, Beatrice Pesquet-Popescu. A parallel proximal splitting method for disparity estimation from multicomponent images under illumination variation. Journal of Mathematical Imaging and Vision, Springer Verlag, 2013, 47 (3), pp.167-178. ⟨10.1007/s10851-012-0361-z⟩. ⟨hal-00733454⟩

Export

BibTeX TEI DC DCterms EndNote

Share

Metrics

Record views

506

Files downloads

364

Contact

Informations

CCSD