A fuzzy approach to oil spill detection an SAR images

Author

Barni, Mauro ; Betti, Michele ; Mecocci, Alessandro

Author_Institution

Dept. of Electron. Eng., Florence Univ., Italy

Volume

1

fYear

34881

fDate

10-14 Jul1995

Firstpage

157

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 used to determine the optimal number of clusters present in the data. A final step involves a cluster merging procedure driven by edge information provided by a Sobel operator. The algorithm has been tested on SEASAT images

Keywords

fuzzy set theory; geophysical signal processing; image segmentation; oceanographic techniques; pollution measurement; radar applications; radar imaging; remote sensing by radar; spaceborne radar; synthetic aperture radar; water pollution measurement; SAR image; Sobel operator; cluster merging; cluster validity criterion; filtering; fuzzy approach; fuzzy clustering; grey level intensities; image processing; image segmentation; marine pollution; measurement technique; ocean; oil spill detection; radar imaging; radar remote sensing; sea surface; speckle noise reduction; synthetic aperture radar; three-step algorithm; Clustering algorithms; Filtering; Image segmentation; Lubricating oils; Noise reduction; Partitioning algorithms; Petroleum; Radar detection; Speckle; Synthetic aperture radar;

fLanguage

English

Publisher

ieee

Conference_Titel

Geoscience and Remote Sensing Symposium, 1995. IGARSS '95. 'Quantitative Remote Sensing for Science and Applications', International

Conference_Location

Firenze

Print_ISBN

0-7803-2567-2

Type

conf

DOI

10.1109/IGARSS.1995.519676

Filename

519676