NDLI: Ship detection with the fuzzy c-mean clustering algorithm using fully polarimetric SAR

Content Provider	IEEE Xplore Digital Library
Author	Haiyan Li Yijun He Hui Shen
Copyright Year	2007
Description	Author affiliation: Chinese Acad. of Sci., Qingdao (Haiyan Li; Yijun He; Hui Shen)
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.
Starting Page	1151
Ending Page	1154
File Size	1476599
Page Count	4
File Format	PDF
ISBN	9781424412112
DOI	10.1109/IGARSS.2007.4423007
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-07-23
Publisher Place	Spain
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Marine vehicles Clustering algorithms Radar detection Polarization Synthetic aperture radar Sea measurements Backscatter Statistical distributions Covariance matrix Euclidean distance Wishart distance Ship detection Fuzzy c-means Polarimetric synthetic aperture radar
Content Type	Text
Resource Type	Article

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