Feature selection via Cramer's V-test discretization for remote-sensing image classification

IEEE Transactions on Geoscience and Remote Sensing

Volumn 52, Issue 5, 2014, Pages 2593-2606

  Wu, Bo ^a   Zhang, Liangpei ^b   Zhao, Yindi ^c  

^a FUZHOU UNIVERSITY   (China)

^b WUHAN UNIVERSITY   (China)

^c CHINA UNIVERSITY OF MINING AND TECHNOLOGY   (China)

Author keywords

Association index; Cramer's V test (CV test); feature discretization; feature selection; image classification

Indexed keywords

ALGORITHMS; DECISION TREES; FEATURE EXTRACTION; REMOTE SENSING; SUPPORT VECTOR MACHINES;

CLASSIFICATION ACCURACY; CRAMER'S V-TEST (CV-TEST); FEATURE DISCRETIZATION; FEATURE SELECTION METHODS; HIGH SPATIAL RESOLUTION IMAGES; REMOTELY SENSED IMAGERY; STATE-OF-THE-ART METHODS; SUPPORT VECTOR MACHINE CLASSIFIERS;

IMAGE CLASSIFICATION;

ACCURACY ASSESSMENT; ALGORITHM; DATA SET; IMAGE CLASSIFICATION; INDEX METHOD; REMOTE SENSING; SPATIAL RESOLUTION;

EID: 84896315238     PISSN: 01962892     EISSN: None     Source Type: Journal    
DOI: 10.1109/TGRS.2013.2263510     Document Type: Article

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