Learning conditional random fields for classification of hyperspectral images

IEEE Transactions on Image Processing

Volumn 19, Issue 7, 2010, Pages 1890-1907

  Zhong, Ping ^a   Wang, Runsheng ^a  

^a NATIONAL UNIVERSITY OF DEFENSE TECHNOLOGY   (China)

Author keywords

Conditional random field (CRF); Contextual information; Hyperpectral image classification; Multinomial logistic regression (MLR); Piecewise training

Indexed keywords

CLASSIFICATION TASKS; CONDITIONAL RANDOM FIELD; CONTEXTUAL INFORMATION; COUNTING PROBLEMS; EXPLICIT MODELING; HYPER-SPECTRAL IMAGES; HYPERSPECTRAL DATA; HYPERSPECTRAL IMAGE CLASSIFICATION; INDEPENDENT CLASSIFIERS; LOCAL METHODS; MULTINOMIAL LOGISTIC REGRESSION; OBSERVED DATA; PIECE-WISE; PROBABILISTIC FRAMEWORK; REAL-WORLD; TRAINING FRAMEWORK; TRAINING METHODS;

CLASSIFIERS; HEURISTIC ALGORITHMS; IMAGE ANALYSIS; IMAGE CLASSIFICATION; IMAGE SEGMENTATION; INDEPENDENT COMPONENT ANALYSIS;

CLASSIFICATION (OF INFORMATION);

EID: 77953710563     PISSN: 10577149     EISSN: None     Source Type: Journal    
DOI: 10.1109/TIP.2010.2045034     Document Type: Article

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