Random Forest and Rotation Forest for fully polarized SAR image classification using polarimetric and spatial features

ISPRS Journal of Photogrammetry and Remote Sensing

Volumn 105, Issue , 2015, Pages 38-53

  Du, Peijun ^a,b   Samat, Alim ^a,b   Waske, Björn ^c   Liu, Sicong ^d   Li, Zhenhong ^e  

^a NANJING UNIVERSITY   (China)

^b NANJING NORMAL UNIVERSITY   (China)

^c FREIE UNIVERSITÄT BERLIN   (Germany)

^d UNIVERSITY OF TRENTO   (Italy)

^e NEWCASTLE UNIVERSITY   (United Kingdom)

Author keywords

Ensemble learning; Image classification; Morphological profiles; Polarimetric SAR; Random Forest; Rotation Forest; Textural feature

Indexed keywords

CLASSIFICATION (OF INFORMATION); COVARIANCE MATRIX; DECISION TREES; DOMAIN DECOMPOSITION METHODS; GEOMETRICAL OPTICS; POLARIMETERS; RADAR IMAGING; REMOTE SENSING; ROTATION; SUPPORT VECTOR MACHINES; SYNTHETIC APERTURE RADAR;

ENSEMBLE LEARNING; MORPHOLOGICAL PROFILE; POLARIMETRIC SAR; RANDOM FORESTS; ROTATION FORESTS; TEXTURAL FEATURE;

IMAGE CLASSIFICATION;

BACKSCATTER; FOREST ECOSYSTEM; HOMOGENEITY; IMAGE CLASSIFICATION; RADARSAT; REMOTE SENSING; RESOLUTION; SPATIAL ANALYSIS; SYNTHETIC APERTURE RADAR; URBAN AREA;

EID: 84927582865     PISSN: 09242716     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.isprsjprs.2015.03.002     Document Type: Article

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