A two-stage feature selection framework for hyperspectral image classification using few labeled samples

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing

Volumn 7, Issue 4, 2014, Pages 1023-1035

  Jia, Sen ^a   Zhu, Zexuan ^a   Shen, Linlin ^a   Li, Qingquan ^a  

^a SHENZHEN UNIVERSITY   (China)

Author keywords

feature extraction; feature selection; Hyperspectral image classification

Indexed keywords

CLUSTERING ALGORITHMS; FACE RECOGNITION; FEATURE EXTRACTION; SPECTROSCOPY;

AFFINITY PROPAGATION CLUSTERING; CLASSIFICATION ACCURACY; COMPLEX-WAVELET STRUCTURAL SIMILARITIES; DISCRIMINATIVE FEATURES; GABOR WAVELET TRANSFORMS; HYPERSPECTRAL IMAGE CLASSIFICATION; SMALL SAMPLE SIZE PROBLEMS; STATE-OF-THE-ART METHODS;

IMAGE CLASSIFICATION;

ALGORITHM; IMAGE ANALYSIS; IMAGE CLASSIFICATION; LAND COVER; PIXEL; SPECTRAL ANALYSIS; WAVELET ANALYSIS;

EID: 84899795478     PISSN: 19391404     EISSN: 21511535     Source Type: Journal    
DOI: 10.1109/JSTARS.2013.2282161     Document Type: Article

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