Title :
Unsupervised classification of PolSAR data using Freeman decomposition and fuzzy clustering
Author :
Tan, Lulu ; Yang, Ruliang
Author_Institution :
Inst. of Electron., Chinese Acad. of Sci., Beijing, China
Abstract :
An unsupervised classification method using Freeman decomposition and fuzzy clustering is proposed to solve the ambiguity problem among surface, volume and double-bounce scattering dominated region. A fuzzy clustering method of PolSAR data making use of scattering power entropy and anisotropy parameters is proposed to partition different scattering mechanisms dominated region. The proposed method is applied to full polarimetric synthetic aperture radar data of Oberpfaffenhofen acquired by ESAR. Experiment result confirms the validity of this method.
Keywords :
entropy; fuzzy set theory; radar polarimetry; scattering; synthetic aperture radar; Freeman decomposition; PolSAR data; anisotropy parameters; double-bounce scattering dominated region; fuzzy clustering; polarimetric synthetic aperture radar; scattering power entropy; unsupervised classification method; Anisotropic magnetoresistance; Classification algorithms; Clustering methods; Covariance matrix; Data mining; Entropy; Pixel; Polarimetric synthetic aperture radar; Radar scattering; Synthetic aperture radar; Freeman decomposition; PolSAR; fuzzy clustering; unsupervised classification;
Conference_Titel :
Synthetic Aperture Radar, 2009. APSAR 2009. 2nd Asian-Pacific Conference on
Conference_Location :
Xian, Shanxi
Print_ISBN :
978-1-4244-2731-4
Electronic_ISBN :
978-1-4244-2732-1
DOI :
10.1109/APSAR.2009.5374123
