Image Denoising with a Constrained Discrete Total Variation Scale Space
This paper describes an approach for performing image restoration using a coupled differential system that both simplifies the image while preserving its contrast. The first process corresponds to a differential inclusion involving discrete Total Variations that simplifies more and more the observed image as time evolves. The second one extracts some pertinent geometric information contained in the series of simplified images and recovers the constrast using Bregman distances. Convergence and exact computational properties of the method rely on the discrete and combinatorial properties of discrete Total Variations.
KeywordsDiscrete Total Variation Bregman Distances Differential Inclusions Network Flows
- 7.Chambolle, A., Lions, P.L.: Image recovery via total variation minimization and related problems. Num. Math. (76), 167–188 (1997)Google Scholar
- 9.Darbon, J.: In preparation. Tech. rep. (2010)Google Scholar
- 10.Darbon, J., Ciril, I., Marquina, A., Chan, T., Osher, S.: A note on the bregmanized total variation and dual forms. In: 16th IEEE International Conference on Image Processing (ICIP), pp. 2965–2968 (November 2009)Google Scholar
- 13.Gilboa, G., Darbon, J., Osher, S., Chan, T.F.: Nonlocal convex functionals for image regularization. Tech. Rep. CAM-06-57, UCLA (October 2006)Google Scholar