Hyperspectral remote sensing image classification based on rotation forest

IEEE Geoscience and Remote Sensing Letters

Volumn 11, Issue 1, 2014, Pages 239-243

  Xia, Junshi ^a,b   Du, Peijun ^c   He, Xiyan ^b   Chanussot, Jocelyn ^b  

^a CHINA UNIVERSITY OF MINING AND TECHNOLOGY   (China)

^b GIPSA LAB   (France)

^c NANJING UNIVERSITY   (China)

Author keywords

Classification; decision tree; ensemble learning; hyperspectral remote sensing image; Rotation Forest

Indexed keywords

ENSEMBLE LEARNING; ENSEMBLE LEARNING APPROACH; FEATURE TRANSFORMATIONS; HYPERSPECTRAL REMOTE SENSING; HYPERSPECTRAL REMOTE SENSING IMAGE; LOCAL FISHER DISCRIMINANT ANALYSIS; MAXIMUM NOISE FRACTION; ROTATION FORESTS;

ADAPTIVE BOOSTING; CLASSIFICATION (OF INFORMATION); DATA MINING; DECISION TREES; FISHER INFORMATION MATRIX; IMAGE CLASSIFICATION; IMAGE RECONSTRUCTION; INDEPENDENT COMPONENT ANALYSIS; METADATA; PRINCIPAL COMPONENT ANALYSIS;

ROTATION;

EID: 84888299612     PISSN: 1545598X     EISSN: None     Source Type: Journal    
DOI: 10.1109/LGRS.2013.2254108     Document Type: Article

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