Variational pairing of image segmentation and blind restoration

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

40 Scopus citations


Segmentation and blind restoration are both classical problems, that are known to be difficult and have attracted major research efforts. This paper shows that the two problems are tightly coupled and can be successfully solved, together. Mutual support of the segmentation and blind restoration processes within a joint variational framework is theoretically motivated, and validated by successful experimental results. The proposed variational method integrates Mumford-Shah segmentation with parametric blur-kernel recovery and image deconvolution. The functional is formulated using the Γ-convergence approximation and is iteratively optimized via the alternate minimization method. While the major novelty of this work is in the unified solution of the segmentation and blind restoration problems, the important special case of known blur is also considered and promising results are obtained.

Original languageEnglish
Title of host publicationComputer Vision - ECCV 2004
Subtitle of host publication8th European Conference on Computer Vision, Prague, Czech Republic, May 11-14, 2004. Proceedings, Part II
EditorsTomáš Pajdla, Jiří Matas
PublisherSpringer Berlin Heidelberg
Number of pages12
ISBN (Electronic)978-3-540-24671-8
ISBN (Print)3540219838, 9783540219835
StatePublished - 2004
Event8th European Conference on Computer Vision, ECCV 2004
- Prague, Czech Republic
Duration: 11 May 200414 May 2004
Conference number: 8

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference8th European Conference on Computer Vision, ECCV 2004
Abbreviated titleECCV 2004
Country/TerritoryCzech Republic


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