Bayesian nonnegative matrix factorization with volume prior for unmixing of hyperspectral images

Machine Learning for Signal Processing XIX - Proceedings of the 2009 IEEE Signal Processing Society Workshop, MLSP 2009

Volumn , Issue , 2009, Pages

  Arngren, Morten ^a,c   Schmidt, Mikkel N ^b   Larsen, Jan ^a  

^a TECHNICAL UNIVERSITY OF DENMARK   (Denmark)

^b UNIVERSITY OF CAMBRIDGE   (United Kingdom)

^c Foss   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BAYESIAN; BAYESIAN FRAMEWORKS; ENDMEMBERS; GIBBS SAMPLING; HYPER-SPECTRAL IMAGES; HYPERSPECTRAL DATA; HYPERSPECTRAL IMAGE ANALYSIS; NONNEGATIVE MATRIX FACTORIZATION; POSTERIOR DISTRIBUTIONS; SPECTRAL SIGNATURE; UNMIXING; VOLUME CONSTRAINT; WHEAT KERNELS;

BAYESIAN NETWORKS; BLIND SOURCE SEPARATION; FACTORIZATION; GRAIN (AGRICULTURAL PRODUCT); IMAGE ANALYSIS; INDEPENDENT COMPONENT ANALYSIS; LEARNING SYSTEMS; LIGHT MEASUREMENT; PIXELS; SIGNAL PROCESSING; TARGET TRACKING; TECHNICAL PRESENTATIONS;

MATRIX ALGEBRA;

EID: 77950919715     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/MLSP.2009.5306262     Document Type: Conference Paper

References (12)

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