Empirical mode decomposition of hyperspectral images for support vector machine classification

IEEE Transactions on Geoscience and Remote Sensing

Volumn 48, Issue 11, 2010, Pages 4071-4084

  Demir, Begüm ^a   Ertürk, Sarp ^a  

^a KOCAELI UNIVERSITY   (Turkey)

Author keywords

Classification; empirical mode decomposition (EMD); hyperspectral images; support vector machines (SVMs)

Indexed keywords

CLASSIFICATION; CLASSIFICATION ACCURACY; COMPOSITE KERNELS; EMPIRICAL MODE DECOMPOSITION; HYPER-SPECTRAL IMAGES; HYPERSPECTRAL; HYPERSPECTRAL IMAGE CLASSIFICATION; INTRINSIC FEATURES; INTRINSIC MODE FUNCTIONS; NONLINEAR AND NON-STATIONARY SIGNALS; SPATIALLY ADAPTIVE; SUPPORT VECTOR; SUPPORT VECTOR MACHINE CLASSIFICATION; SVM CLASSIFICATION;

CLASSIFICATION (OF INFORMATION); GEARS; IMAGE ANALYSIS; INDEPENDENT COMPONENT ANALYSIS; POWER QUALITY; VECTORS;

SUPPORT VECTOR MACHINES;

ACCURACY ASSESSMENT; EMPIRICAL ANALYSIS; IMAGE ANALYSIS; IMAGE CLASSIFICATION; IMF; MACHINERY; NONLINEARITY; PERFORMANCE ASSESSMENT; SPECTRAL ANALYSIS; VECTOR;

EID: 78049253494     PISSN: 01962892     EISSN: None     Source Type: Journal    
DOI: 10.1109/TGRS.2010.2070510     Document Type: Article

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