Global Minimization of the Active Contour Model with TV-Inpainting and Two-Phase Denoising
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The active contour model [8,9,2] is one of the most well-known variational methods in image segmentation. In a recent paper by Bresson et al. , a link between the active contour model and the variational denoising model of Rudin-Osher-Fatemi (ROF)  was demonstrated. This relation provides a method to determine the global minimizer of the active contour model. In this paper, we propose a variation of this method to determine the global minimizer of the active contour model in the case when there are missing regions in the observed image. The idea is to turn off the L 1-fidelity term in some subdomains, in particular the regions for image inpainting. Minimizing this energy provides a unified way to perform image denoising, segmentation and inpainting.
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- 1.Bresson, X., Esedoḡlu, S., Vandergheynst, P., Thiran, J.P., Osher, S.: Global minimizers of the active contour/snake model. UCLA CAM Report (05-04) (2005)Google Scholar
- 3.Chan, R., Ho, C.-W., Nikolova, M.: Salt-and-pepper noise removal by median-type noise detectors and detail-preserving regularization. In preparation (2004)Google Scholar
- 4.Chan, R., Hu, C., Nikolova, M.: An iterative procedure for removing random-valued impuse noise. In preparation (2004)Google Scholar
- 5.Chan, T.F., Esedoḡlu, S., Nikolova, M.: Algorithms for finding global minimizers of image segmentation and denoising models. UCLA CAM Report (04-54) (2004)Google Scholar
- 6.Chan, T.F., Kang, S.H.: Error analysis for image inpainting. UCLA CAM Report (04-72) (2004)Google Scholar