Mahalanobis kernel for the classification of hyperspectral images

International Geoscience and Remote Sensing Symposium (IGARSS)

Volumn , Issue , 2010, Pages 3724-3727

  Fauvel, M ^a   Villa, A ^b,c   Chanussot, J ^b   Benediktsson, J A ^c  

^a INRIA RHÔNE ALPES   (France)

^b GRENOBLE INSTITUTE OF TECHNOLOGY   (France)

^c UNIVERSITY OF ICELAND   (Iceland)

Author keywords

Classification; Hyper spectral images; Mahalanobis kernel; Probabilistic principal component analysis; Support vector machine

Indexed keywords

CLASSIFICATION (OF INFORMATION); COVARIANCE MATRIX; INVERSE PROBLEMS; REMOTE SENSING; SPECTROSCOPY; SUPPORT VECTOR MACHINES;

CLASSIFICATION ACCURACY; FIRST PRINCIPAL COMPONENTS; HYPER-SPECTRAL IMAGES; HYPERSPECTRAL REMOTE SENSING IMAGE; MAHALANOBIS; PRINCIPAL DIRECTIONS; PROBABILISTIC MODELING; PROBABILISTIC PRINCIPAL COMPONENT ANALYSIS;

IMAGE CLASSIFICATION;

EID: 78650897460     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IGARSS.2010.5651956     Document Type: Conference Paper

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