Abstract
The fuzzy c-medians clustering (FCMED) clustering algorithm is known to be a robust l/sub 1/ fuzzy clustering algorithm that works well even in the presence of outliers or remote small clusters. The well-known fuzzy c-means (FCM) clustering algorithm often performs poorly in this environment. Unfortunately, the FCMED has a high space-complexity, which makes its application impractical for large images. A new fast fuzzy c-medians clustering (FFCMED) algorithm is presented, which may be applied to any clustering problem, but is demonstrated here by classifying a POLSAR image. The FFCMED provides a robust clustering tool that works well for large images and data sets. A relative speed up over the FCMED of at least 3-to-1 was observed for the image illustrated in this paper.
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