Finding the global minimum for binary image restoration

Tony Chan*, Selim Esedoglu, Mila Nikolova

*Corresponding author for this work

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

20 Scopus citations

Abstract

Restoring binary images is a problem which arises in various application fields. In our paper, this problem is considered in a variational framework: the sought-after solution minimizes an energy. Energies defined over the set of the binary images are inevitably nonconvex and there are no general methods to calculate the global minimum, while local minimziers are very often of limited interest. In this paper we define the restored image as the global minimizer of the total-variation (TV) energy functional constrained to the collection of all binary-valued images. We solve this constrained non-convex optimization problem by deriving another functional which is convex and whose (unconstrained) minimum is proven to be reached for the global minimizer of the binary constrained TV functional. Practical issues are discussed and a numerical example is provided.

Original languageEnglish (US)
Title of host publicationIEEE International Conference on Image Processing 2005, ICIP 2005
Pages121-124
Number of pages4
DOIs
StatePublished - Dec 1 2005
EventIEEE International Conference on Image Processing 2005, ICIP 2005 - Genova, Italy
Duration: Sep 11 2005Sep 14 2005

Publication series

NameProceedings - International Conference on Image Processing, ICIP
Volume1
ISSN (Print)1522-4880

Conference

ConferenceIEEE International Conference on Image Processing 2005, ICIP 2005
CountryItaly
CityGenova
Period09/11/0509/14/05

ASJC Scopus subject areas

  • Engineering(all)

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