Adaptive support vector machine and Markov random field model for classifying hyperspectral imagery

Journal of Applied Remote Sensing

Volumn 5, Issue 1, 2011, Pages

  Li, Shanshan ^a   Zhang, Bing ^a   Chen, Dongmei ^b   Gao, Lianru ^a   Peng, Man ^c  

^a CENTER FOR EARTH OBSERVATION AND DIGITAL EARTH   (China)

^b QUEEN S UNIVERSITY   (Canada)

^c INSTITUTE OF REMOTE SENSING APPLICATIONS   (China)

Author keywords

hyperspectral; image classification; Markov random field; support vector machine

Indexed keywords

CLASSIFICATION (OF INFORMATION); COVARIANCE MATRIX; IMAGE ENHANCEMENT; IMAGE SEGMENTATION; MAGNETORHEOLOGICAL FLUIDS; MARKOV PROCESSES; MAXIMUM LIKELIHOOD ESTIMATION; PIXELS; REMOTE SENSING; SPECTROSCOPY; SUPPORT VECTOR MACHINES;

CLASSIFICATION ACCURACY; CONTEXTUAL INFORMATION; HYPER-SPECTRAL IMAGERIES; HYPERSPECTRAL; MARKOV RANDOM FIELD MODEL; MARKOV RANDOM FIELDS; MAXIMUM LIKELIHOOD CLASSIFIERS; REMOTE SENSING IMAGE CLASSIFICATION;

IMAGE CLASSIFICATION;

EID: 84855223458     PISSN: None     EISSN: 19313195     Source Type: Journal    
DOI: 10.1117/1.3609847     Document Type: Article

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