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Multiresolution image segmentation integrating Gibbs sampler and region merging algorithm

journal contribution
posted on 2003-01-01, 00:00 authored by Chang-Tsun LiChang-Tsun Li
This work approaches the texture segmentation problem by incorporating Gibbs sampler (i.e., the combination of Markov random fields and simulated annealing) and a region-merging process within a multiresolution structure with "high class resolution and low boundary resolution" at high levels and "low class resolution and high boundary resolution" at lower ones. As the algorithm descends the multiresolution structure, the coarse segmentation results are propagated down to the lower levels so as to reduce the inherent class-boundary uncertainty and to improve the segmentation accuracy. The computational complexity and frequent occurrences of over-segmentation of Gibbs sampler are addressed and the computationally and functionally effective region-merging process is included to allow Gibbs sampler to start its annealing schedule at relatively low pseudo-temperature and to guide the search trajectory away from local minima associated with over-segmented configurations. © 2002 Elsevier Science B.V. All rights reserved.

History

Journal

Signal processing

Volume

83

Pagination

67-78

Location

Amsterdam, The Netherlands

ISSN

0165-1684

Language

eng

Publication classification

C1.1 Refereed article in a scholarly journal

Copyright notice

2002, Elsevier Science B.V.

Issue

1

Publisher

Elsevier

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