Title :
Fuzzy segmentation of SAR images for oil spill recognition
Author :
Barni, A. ; Betti, M. ; Mecocci, A.
Author_Institution :
Florence Univ., Italy
Abstract :
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
Keywords :
filtering theory; fuzzy set theory; image recognition; image segmentation; radar imaging; speckle; synthetic aperture radar; SAR images; SEASAT images; Sobel operator; cluster merging procedure; cluster validity criterion; edge information; filtering; fuzzy clustering; fuzzy segmentation; grey level intensities; marine background; oil spill recognition; speckle noise reduction; three-step algorithm;
Conference_Titel :
Image Processing and its Applications, 1995., Fifth International Conference on
Conference_Location :
Edinburgh
Print_ISBN :
0-85296-642-3
DOI :
10.1049/cp:19950716