Hyperspectral Image Classification Using Fast and Adaptive Bidimensional Empirical Mode Decomposition with Minimum Noise Fraction

IEEE Geoscience and Remote Sensing Letters

Volumn 13, Issue 12, 2016, Pages 1950-1954

  Yang, Ming Der ^a   Huang, Kai Shiang ^a   Yang, Yeh Fen ^a   Lu, Liang You ^a   Feng, Zheng Yi ^a   Tsai, Hui Ping ^a  

^a NATIONAL CHUNG HSING UNIVERSITY   (Taiwan)

Author keywords

Empirical mode decomposition (EMD); fast and adaptive bidimensional EMD (FABEMD); hyperspectral image classification; minimum noise fraction (MNF); support vector machine (SVM)

Indexed keywords

AUDIO SIGNAL PROCESSING; CLASSIFICATION (OF INFORMATION); IMAGE PROCESSING; INDEPENDENT COMPONENT ANALYSIS; INFRARED IMAGING; LOW PASS FILTERS; SIGNAL PROCESSING; SPECTROSCOPY; SUPPORT VECTOR MACHINES; THERMOGRAPHY (IMAGING);

AIRBORNE VISIBLE INFRARED IMAGING SPECTROMETER; BI-DIMENSIONAL EMPIRICAL MODE DECOMPOSITIONS; CLASSIFICATION ACCURACY; CLASSIFICATION RESULTS; HYPERSPECTRAL IMAGE CLASSIFICATION; INTRINSIC MODE FUNCTIONS; MINIMUM NOISE FRACTION; SUPPORT VECTOR MACHINE CLASSIFIERS;

IMAGE CLASSIFICATION;

EID: 84995460862     PISSN: 1545598X     EISSN: None     Source Type: Journal    
DOI: 10.1109/LGRS.2016.2618930     Document Type: Article

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