Name
Abstract | ||
|---|---|---|
This paper deals with the minimization of the total variation under a convex data fidelity term. We propose an algorithm which computes an exact minimizer of this problem. The method relies on the decomposition of an image into its level sets. Using these level sets, we map the problem into optimizations of independent binary Markov Random Fields. Binary solutions are found thanks to graph-cut techniques and we show how to derive a fast algorithm. We also study the special case when the fidelity term is the L1-norm. Finally we provide some experiments. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1007/11492429_43 | IbPRIA (1) |
Keywords | Field | DocType |
markov random fields,fidelity term,special case,convex data,paper deal,binary solution,exact minimizer,fast algorithm,level set,exact algorithm,total variation minimization,independent binary,graph cut,total variation | Markov process,Random field,Exact algorithm,Computer science,Markov random field,Markov chain,Level set,Algorithm,Image segmentation,Binary number | Conference |
Volume | ISSN | ISBN |
3522 | 0302-9743 | 3-540-26153-2 |
Citations | PageRank | References |
35 | 8.03 | 14 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jérôme Darbon | 1 | 512 | 41.96 |
| Marc Sigelle | 2 | 316 | 34.12 |