Bayesian segmentation of hyperspectral images

Details Bayesian segmentation of hyperspectral images Bayesian segmentation of hyperspectral images

2007-08-22

arxiv.org/abs/0708.3013v1

Physics

Data Analysis, Statistics and Probability

8 pages, 2 figures, presented at MaxEnt 2004, Inst. Max Planck, Garching, Germany

Scientific paper

In this paper we consider the problem of joint segmentation of hyperspectral images in the Bayesian framework. The proposed approach is based on a Hidden Markov Modeling (HMM) of the images with common segmentation, or equivalently with common hidden classification label variables which is modeled by a Potts Markov Random Field. We introduce an appropriate Markov Chain Monte Carlo (MCMC) algorithm to implement the method and show some simulation results.

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