Subspace-based support vector machines for hyperspectral image classification

IEEE Geoscience and Remote Sensing Letters

Volumn 12, Issue 2, 2015, Pages 349-353

  Gao, Lianru ^a   Li, Jun ^b   Khodadadzadeh, Mahdi ^c   Plaza, Antonio ^c   Zhang, Bing ^a   He, Zhijian ^b   Yan, Huiming ^a  

^a INSTITUTE OF GEOLOGY AND GEOPHYSICS   (China)

^b SUN YAT SEN UNIVERSITY   (China)

^c UNIVERSITY OF EXTREMADURA   (Spain)

Author keywords

Hyperspectral image classification; multinomial logistic regression (MLR); subspace based approaches; support vector machines (SVMs)

Indexed keywords

IMAGE CLASSIFICATION; IMAGE RECONSTRUCTION; NASA; REGRESSION ANALYSIS; SAMPLING; SPECTROSCOPY;

AIRBORNE VISIBLE/INFRARED IMAGING SPECTROMETERS; HIGH DIMENSIONALITY; HYPERSPECTRAL IMAGE CLASSIFICATION; MULTINOMIAL LOGISTIC REGRESSION; NONLINEAR FUNCTIONS; REMOTE SENSING IMAGE CLASSIFICATION; SUBSPACE-BASED APPROACHES; SUPPORT VECTOR MACHINE (SVMS);

SUPPORT VECTOR MACHINES;

EID: 84906949283     PISSN: 1545598X     EISSN: None     Source Type: Journal    
DOI: 10.1109/LGRS.2014.2341044     Document Type: Article

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