Hyperspectral Image Classification with Canonical Correlation Forests

IEEE Transactions on Geoscience and Remote Sensing

Volumn 55, Issue 1, 2017, Pages 421-431

  Xia, Junshi ^a   Yokoya, Naoto ^a   Iwasaki, Akira ^a  

^a UNIVERSITY OF TOKYO   (Japan)

Author keywords

Canonical correlation forests (CCF); classification; ensemble learning; hyperspectral image

Indexed keywords

BINARY TREES; DECISION TREES; HYPERSPECTRAL IMAGING; IMAGE CLASSIFICATION; INDEPENDENT COMPONENT ANALYSIS; MARKOV PROCESSES; REMOTE SENSING; SPECTROSCOPY;

CANONICAL CORRELATIONS; CLASSIFICATION RESULTS; COMPARATIVE EFFECTIVENESS; ENSEMBLE LEARNING; HYPERSPECTRAL REMOTE SENSING IMAGE; MARKOV RANDOM FIELDS; MULTIPLE CLASSIFIER SYSTEMS; SPECTRAL INFORMATION;

CLASSIFICATION (OF INFORMATION);

ACCURACY ASSESSMENT; BOOTSTRAPPING; CANONICAL ANALYSIS; COMPLEXITY; DATA SET; EXPERIMENTAL STUDY; IMAGE CLASSIFICATION; LEARNING; MARKOV CHAIN; MULTISPECTRAL IMAGE; REMOTE SENSING;

EID: 84990845557     PISSN: 01962892     EISSN: None     Source Type: Journal    
DOI: 10.1109/TGRS.2016.2607755     Document Type: Article

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