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 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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© 2005 Springer-Verlag Berlin Heidelberg
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Leung, S., Osher, S. (2005). Global Minimization of the Active Contour Model with TV-Inpainting and Two-Phase Denoising. In: Paragios, N., Faugeras, O., Chan, T., Schnörr, C. (eds) Variational, Geometric, and Level Set Methods in Computer Vision. VLSM 2005. Lecture Notes in Computer Science, vol 3752. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11567646_13
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DOI: https://doi.org/10.1007/11567646_13
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-29348-4
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