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Joint segmentation of multiple images with shared classes: a Bayesian nonparametrics approach

Sodjo, Jessica and Giremus, Audrey and Caron, François and Giovannelli, Jean-François and Dobigeon, Nicolas Joint segmentation of multiple images with shared classes: a Bayesian nonparametrics approach. (2016) In: IEEE Workshop on statistical signal processing (SSP 2016), 26 June 2016 - 29 June 2016 (Palma de Mallorca, Spain).

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Official URL: http://dx.doi.org/10.1109/SSP.2016.7551735

Abstract

A combination of the hierarchical Dirichlet process (HDP) and the Potts model is proposed for the joint segmentation/classification of a set of images with shared classes. Images are first divided into homogeneous regions that are assumed to belong to the same class when sharing common characteristics. Simultaneously, the Potts model favors configurations defined by neighboring pixels belonging to the same class. This HDP-Potts model is elected as a prior for the images, which allows the best number of classes to be selected automatically. A Gibbs sampler is then designed to approximate the Bayesian estimators, under a maximum a posteriori (MAP) paradigm. Preliminary experimental results are finally reported using a set of synthetic images.

Item Type:Conference or Workshop Item (Paper)
Additional Information:Thanks to IEEE editor. The definitive version is available at http://ieeexplore.ieee.org This papers appears in Proceedings of IEEE SSP 2016. Electronic ISBN: 978-1-4673-7803-1 The original PDF of the article can be found at: http://ieeexplore.ieee.org/document/7551735/ Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
HAL Id:hal-01500506
Audience (conference):International conference proceedings
Uncontrolled Keywords:
Institution:Other partners > Bordeaux INP - BINP (FRANCE)
French research institutions > Centre National de la Recherche Scientifique - CNRS (FRANCE)
Université de Toulouse > Institut National Polytechnique de Toulouse - INPT (FRANCE)
Université de Toulouse > Université Toulouse III - Paul Sabatier - UPS (FRANCE)
Université de Toulouse > Université Toulouse - Jean Jaurès - UT2J (FRANCE)
Université de Toulouse > Université Toulouse 1 Capitole - UT1 (FRANCE)
Other partners > Université de Bordeaux (FRANCE)
Other partners > University of Oxford (UNITED KINGDOM)
Laboratory name:
Statistics:download
Deposited By: IRIT IRIT
Deposited On:13 Mar 2017 08:05

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