Towards a Sparse Bayesian Markov Random Field Approach to Hyperspectral Unmixing and Classification.

Abstract

Recent work has shown that existing powerful Bayesian hyperspectral unmixing frameworks can be significantly improved by incorporating the inherent local spatial correlations between pixel class labels via the use of Markov random fields. We here propose a new Bayesian approach to joint hyperspectral unmixing and image classification, such that the previous… (More)

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