Global minimization of the active contour model with TV-Inpainting and two-phase denoising

Authors:
Shingyu Leung;Stanley Osher
Affiliations:
Department of Mathematics, UCLA, Los Angeles, CA;Department of Mathematics, UCLA, Los Angeles, CA
Venue:
VLSM'05 Proceedings of the Third international conference on Variational, Geometric, and Level Set Methods in Computer Vision
Year:
2005

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Abstract

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. [1], a link between the active contour model and the variational denoising model of Rudin-Osher-Fatemi (ROF) [10] 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 L1-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.