Estimating the number of endmembers in hyperspectral images using the normal compositional model and a hierarchical bayesian algorithm

IEEE Journal on Selected Topics in Signal Processing

Volumn 4, Issue 3, 2010, Pages 582-591

  Eches, Olivier ^a   Dobigeon, Nicolas ^a   Tourneret, Jean Yves ^a  

^a UNIVERSITÉ DE TOULOUSE   (France)

Author keywords

Bayesian inference; Hyperspectral images; Monte Carlo methods; Normal compositional model; Reversible jump; Spectral unmixing

Indexed keywords

BAYESIAN INFERENCE; COMPOSITIONAL MODELS; HYPER-SPECTRAL IMAGES; REVERSIBLE JUMP; SPECTRAL UNMIXING;

ALGORITHMS; BAYESIAN NETWORKS; INFERENCE ENGINES; UNCERTAINTY ANALYSIS;

MONTE CARLO METHODS;

EID: 77952595305     PISSN: 19324553     EISSN: None     Source Type: Journal    
DOI: 10.1109/JSTSP.2009.2038212     Document Type: Article

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