Name
Abstract | ||
|---|---|---|
Stereo matching is an active area of research in image processing. In a recent work, a convex programming approach was developed in order to generate a dense disparity field. In this paper, we address the same estimation problem and propose to solve it in a more general convex optimization framework based on proximal methods. More precisely, unlike previous works where the criterion must satisfy some restrictive conditions in order to be able to numerically solve the minimization problem, this work offers a great flexibility in the choice of the involved criterion. The method is validated in a stereo image coding framework, and the results demonstrate the good performance of the proposed parallel proximal algorithm. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/ICASSP.2011.5946538 | ICASSP |
Keywords | Field | DocType |
convex programming,estimation theory,image coding,image matching,minimisation,parallel algorithms,stereo image processing,convex programming,dense disparity field,depth estimation,image processing,minimization problem,parallel proximal algorithm,proximal splitting method,stereo image coding,stereo matching,Stereo vision,convex programming,disparity estimation,parallel proximal algorithm,proximity operator,variational methods | Mathematical optimization,Stereopsis,Computer science,Parallel algorithm,Image processing,Proximal Gradient Methods,Minimisation (psychology),Pixel,Estimation theory,Convex optimization | Conference |
ISSN | Citations | PageRank |
1520-6149 | 2 | 0.47 |
References | Authors | |
7 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mireille El Gheche | 1 | 14 | 6.39 |
| Jean-Christophe Pesquet | 2 | 560 | 46.10 |
| Joumana Farah | 3 | 158 | 17.80 |
| Mounir Kaaniche | 4 | 74 | 13.41 |
| Béatrice Pesquet-Popescu | 5 | 876 | 91.43 |