Fuzzy segmentation of SAR images for oil spill recognition

A three-step algorithm is developed to segment oil spills from a marine background on Synthetic Aperture Radar (SAR) data. First, filtering is performed to reduce speckle noise. Then fuzzy clustering is carried out to obtain a preliminary partition of the pixels on the basis of their grey level intensities. A very simple cluster validity criterion is tested to determine the optimal number of clusters present in the data. In order to improve segmentation a final step involves a cluster merging procedure using edge information provided by a Sobel operator. The algorithm has been tested on SEASAT images.<
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