A level set algorithm for minimizing the Mumford-Shah functional in image processing

By Tony F. Chan, Luminita A. Vese. Proceedings IEEE Workshop on Variational and Level Set Methods in Computer Vision, 2001

311 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition, Immunology and Allergy

View Paper: https://www.semanticscholar.org/paper/628b0b717bbc37a29c2147015fc411e07c288036

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In Computer Vision and Pattern Recognition

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Citations in the corpus

A survey on level set methods for inverse problems and optimal design (2005, unknown): “[101, 99, 38, 39, 72] for level set based solution methods).”
Geodesic Active Regions and Level Set Methods for Supervised Texture Segmentation (2002, methodology): “Finally, more recent approaches related with the proposed framework can be found in Tsai et al. (2000) and Chan and Vese (2001).”
Curve evolution implementation of the Mumford-Shah functional for image segmentation, denoising, interpolation, and magnification (2001, result): “In [10], [11], multiphase level set techniques are implemented to capture triple points and holes in a very elegant manner.”
Using Prior Shapes in Geometric Active Contours in a Variational Framework (2002, methodology): “…derived by minimizing a generalized Bayes/MDL criterion using the variational principle. cancel: One of the The region-based methods proposed in Cremers (2001), Chan (2001), Chan and Vese (2001), and Tsai (2001) are an active contour based on minimizing the Mumford-Shah functional (Mumford, 1989).”
Diffusion Snakes: Introducing Statistical Shape Knowledge into the Mumford-Shah Functional (2002, background): “, 1995), homogeneity requirements on the statistics of the regions being segmented (Mumford and Shah, 1989; Zhu and Yuille, 1996; Chan and Vese, 2001; Yezzi et al., 2002) or a combination of both (Paragios and Dériche, 2000).”
Mathematical Models for Local Nontexture Inpaintings (2002, methodology): “Among the many exisiting computational methods, here we outline the level-set method of Osher and Sethian 34], as recently applied to the numerical segmentations by Chan and Vese 10], where interested readers can nd more details.”