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

Tony Chan, L. A. Vese

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

171 Scopus citations

Abstract

We show how the piecewise-smooth Mumford-Shah segmentation problem can be solved using the level set method of Osher and Sethian (1988). The obtained algorithm can be simultaneously used to denoise, segment, detect-extract edges, and perform active contours. The proposed model is also a generalisation of a previous active contour model without edges, proposed by the authors in Chan et al., (2001), and of its extension to the case with more than two segments for piecewise-constant segmentation Chan et al., (2000). Based on the four color theorem, we can assume that in general, at most two level set functions are sufficient to detect and represent distinct objects of distinct intensities, with triple junctions, or T-junctions.

Original languageEnglish (US)
Title of host publicationProceedings - IEEE Workshop on Variational and Level Set Methods in Computer Vision, VLSM 2001
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages161-168
Number of pages8
ISBN (Electronic)076951278X, 9780769512785
DOIs
StatePublished - Jan 1 2001
EventIEEE Workshop on Variational and Level Set Methods in Computer Vision, VLSM 2001 - Vancouver, Canada
Duration: Jul 13 2001 → …

Publication series

NameProceedings - IEEE Workshop on Variational and Level Set Methods in Computer Vision, VLSM 2001

Conference

ConferenceIEEE Workshop on Variational and Level Set Methods in Computer Vision, VLSM 2001
CountryCanada
CityVancouver
Period07/13/01 → …

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Computer Vision and Pattern Recognition

Fingerprint

Dive into the research topics of 'A level set algorithm for minimizing the Mumford-Shah functional in image processing'. Together they form a unique fingerprint.

Cite this