Learning sparse CRFs for feature selection and classification of hyperspectral imagery

IEEE Transactions on Geoscience and Remote Sensing

Volumn 46, Issue 12, 2008, Pages 4186-4197

  Zhong, Ping ^a   Wang, Runsheng ^a  

^a NATIONAL UNIVERSITY OF DEFENSE TECHNOLOGY   (China)

Author keywords

Conditional random field (CRF); Contextual information; Feature selection; Hyperspectral image; Image classification; Machine learning; Multinomial logistic regression (MLR); Sparse CRF (SCRF)

Indexed keywords

CONDITIONAL RANDOM FIELD; CONTEXTUAL INFORMATION; FEATURE SELECTION; HYPER-SPECTRAL IMAGES; MACHINE LEARNING; MULTINOMIAL LOGISTIC REGRESSION (MLR); SPARSE CRF (SCRF);

DATA REDUCTION; INDEPENDENT COMPONENT ANALYSIS; PARAMETER ESTIMATION; REMOTE SENSING;

FEATURE EXTRACTION;

EID: 69949122268     PISSN: 01962892     EISSN: None     Source Type: Journal    
DOI: 10.1109/TGRS.2008.2001921     Document Type: Article

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