Bayesian image segmentation using MRF's combined with hierarchical prior models

Authors:
Kohta Aoki;Hiroshi Nagahashi
Affiliations:
Interdisciplinary Graduate School of Science and Engineering, Tokyo Institute of Technology;Imaging Science and Engineering Laboratory, Tokyo Institute of Technology, Yokohama, Japan
Venue:
SCIA'05 Proceedings of the 14th Scandinavian conference on Image Analysis
Year:
2005

Citing 2
Cited 0

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Abstract

The problem of image segmentation can be formulated in the framework of Bayesian statistics. We use a Markov random field as the prior model of the spacial relationship between image pixels, and approximate an observed image by a Gaussian mixture model. In this paper, we introduce into the statistical model a hierarchical prior structure from which model parameters are regarded as drawn. This would give an efficient Gibbs sampler for exploring the joint posterior distribution of all parameters given an observed image and could make the estimation more robust.