Spectral Contextual Classification of Hyperspectral Imagery With Probabilistic Relaxation Labeling

Abstract

In this paper, a spectral-spatial classification framework based on probabilistic relaxation labeling using compatibility coefficients is proposed for hyperspectral images. It is a two-stage classifier that uses maximum <italic>a posteriori</italic> (MAP) estimation to maximize posterior probabilities of classification map obtained in first stage to… (More)
DOI: 10.1109/TCYB.2016.2609882

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