A graph-cut based algorithm for approximate MRF optimization

This paper copes with the approximate minimization of Markovian energy with pairwise interactions. We extend previous approaches that rely on graph-cuts and move making techniques. For this purpose, a new move is introduced that permits us to perform better approximate optimizations. Some experiment...

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Bibliographic Details
Published in2009 16th IEEE International Conference on Image Processing (ICIP) pp. 2413 - 2416
Main Authors Shabou, A., Tupin, F., Darbon, J.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.11.2009
Subjects
Graph-cut
Image denoising
Image restoration
Image segmentation
Iterative algorithms
Lattices
Markov random fields
Minimization methods
Optimization methods
Partitioning algorithms
Telecommunications
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ISBN9781424456536
1424456533
ISSN1522-4880
DOI10.1109/ICIP.2009.5414189

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Summary:This paper copes with the approximate minimization of Markovian energy with pairwise interactions. We extend previous approaches that rely on graph-cuts and move making techniques. For this purpose, a new move is introduced that permits us to perform better approximate optimizations. Some experiments show that very good local minima are obtained while keeping the memory usage low.
ISBN:9781424456536
1424456533
ISSN:1522-4880
DOI:10.1109/ICIP.2009.5414189