Difference between revisions of "Publications/darbon.04.iwcia"
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| lrdeprojects = Olena |
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− | | abstract = This paper deals with the total variation minimization problem when the fidelity is either the |
+ | | abstract = This paper deals with the total variation minimization problem when the fidelity is either the L^2-norm or the L^1-norm. We propose an algorithm which computes the exact solution of these two problems after discretization. Our method relies on the decomposition of an image into its level sets. It maps the original problems into independent binary Markov Random Field optimization problems associated with each level set. Exact solutions of these binary problems are found thanks to minimum-cut techniques. We prove that these binary solutions are increasing and thus allow to reconstruct the solution of the original problems. |
| lrdekeywords = Image |
| lrdekeywords = Image |
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| lrdenewsdate = 2004-09-01 |
| lrdenewsdate = 2004-09-01 |
Revision as of 16:20, 5 January 2018
- Authors
- Jérôme Darbon, Marc Sigelle
- Where
- Proceedings of the 10th International Workshop on Combinatorial Image Analysis (IWCIA)
- Place
- Auckland, New Zealand
- Type
- inproceedings
- Publisher
- Springer-Verlag
- Projects
- Olena
- Keywords
- Image
- Date
- 2004-09-01
Abstract
This paper deals with the total variation minimization problem when the fidelity is either the L^2-norm or the L^1-norm. We propose an algorithm which computes the exact solution of these two problems after discretization. Our method relies on the decomposition of an image into its level sets. It maps the original problems into independent binary Markov Random Field optimization problems associated with each level set. Exact solutions of these binary problems are found thanks to minimum-cut techniques. We prove that these binary solutions are increasing and thus allow to reconstruct the solution of the original problems.
Bibtex (lrde.bib)
@InProceedings{ darbon.04.iwcia, author = {J\'er\^ome Darbon and Marc Sigelle}, title = {Exact optimization of discrete constrained total variation minimization problems}, booktitle = {Proceedings of the 10th International Workshop on Combinatorial Image Analysis (IWCIA)}, year = 2004, address = {Auckland, New Zealand}, month = dec, pages = {548--557}, editors = {R. Klette and J. Zunic}, series = {Lecture Notes in Computer Science Series}, publisher = {Springer-Verlag}, volume = 3322, abstract = {This paper deals with the total variation minimization problem when the fidelity is either the $L^2$-norm or the $L^1$-norm. We propose an algorithm which computes the exact solution of these two problems after discretization. Our method relies on the decomposition of an image into its level sets. It maps the original problems into independent binary Markov Random Field optimization problems associated with each level set. Exact solutions of these binary problems are found thanks to minimum-cut techniques. We prove that these binary solutions are increasing and thus allow to reconstruct the solution of the original problems.} }