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arXiv · 0708.3013

Bayesian segmentation of hyperspectral images

Adel Mohammadpour·Olivier Féron·Ali Mohammad-Djafari
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Abstract

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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Adel Mohammadpour, Olivier Féron, Ali Mohammad-Djafari. 2007-08-22. Bayesian segmentation of hyperspectral images. https://arxiv.org/abs/0708.3013

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