DocumentCode :
2666930
Title :
Ship detection with the fuzzy c-mean clustering algorithm using fully polarimetric SAR
Author :
Li, Haiyan ; He, Yijun ; Shen, Hui
Author_Institution :
Chinese Acad. of Sci., Qingdao
fYear :
2007
fDate :
23-28 July 2007
Firstpage :
1151
Lastpage :
1154
Abstract :
A fuzzy c-mean clustering algorithm to detect ships is proposed using fully polarimetric SAR data. The algorithm is unsupervised. It does not need the statistical decision and the performance is not data specific, as often arises with CFAR methods. A distance measure, based on a complex Wishart distribution, is applied using the fuzzy c-means clustering algorithm. The algorithm makes use the statistical properties of polarimetric data, and takes advantage of a clustering algorithm. It is thus expected that the algorithm could include fully polarimetric backscattering information for ship detection. Its effectiveness is demonstrated by applying it to detect the targets in a set of AIRS AR data.
Keywords :
backscatter; fuzzy set theory; object detection; oceanographic techniques; pattern clustering; radar detection; radar polarimetry; ships; statistical distributions; synthetic aperture radar; AIRS AR data; Wishart distribution; distance measure; fully polarimetric SAR; fuzzy c-mean clustering algorithm; polarimetric backscattering information; polarimetric data; ship detection; statistical decision; unsupervised clustering; Backscatter; Clustering algorithms; Covariance matrix; Euclidean distance; Marine vehicles; Polarization; Radar detection; Sea measurements; Statistical distributions; Synthetic aperture radar; Fuzzy c-means; Polarimetric synthetic aperture radar; Ship detection; Wishart distance;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Geoscience and Remote Sensing Symposium, 2007. IGARSS 2007. IEEE International
Conference_Location :
Barcelona
Print_ISBN :
978-1-4244-1211-2
Electronic_ISBN :
978-1-4244-1212-9
Type :
conf
DOI :
10.1109/IGARSS.2007.4423007
Filename :
4423007
Link To Document :
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