DocumentCode :
2904055
Title :
Oil-spills detection in SAR images by fractal dimension estimation
Author :
Benelli, Giuliano ; Garzelli, Andrea
Author_Institution :
Dept. of Inf. Eng., Siena Univ., Italy
Volume :
1
fYear :
1999
fDate :
1999
Firstpage :
218
Abstract :
The paper describes a multi-resolution algorithm based on fractal geometry for texture analysis and detection of oil spills in SAR images. The multi-resolution approach reduces the problems of speckle and sea clutter and preserves subtle variations of oil slicks. The use of fractal dimension as a feature for classification improves the oil spill detection, since enhances texture discrimination. The proposed approach computes the fractal dimension from power spectra: the ratio between powers at different scales is straightforwardly related to fractal dimension. The proposed method to compute a fractal signature is based on the multi-scale image decomposition obtained by the normalized Laplacian pyramid which provides a reliable estimation of the fractal dimension even in the presence of speckle
Keywords :
environmental science computing; feature extraction; fractals; geophysical signal processing; image classification; image texture; oceanographic techniques; radar imaging; remote sensing by radar; synthetic aperture radar; water pollution measurement; SAR image; feature extraction; fractal dimension; fractal dimension estimation; fractals; image classification; image texture analysis; marine pollution; measurement technique; multi-resolution algorithm; normalized Laplacian pyramid; ocean; oil pollution; oil slick; oil spill; radar imaging; radar remote sensing; sea clutter; speckle; synthetic aperture radar; water pollution; Fractals; Image analysis; Image texture analysis; Ocean temperature; Petroleum; Pixel; Rough surfaces; Sea surface; Speckle; Surface roughness;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Geoscience and Remote Sensing Symposium, 1999. IGARSS '99 Proceedings. IEEE 1999 International
Conference_Location :
Hamburg
Print_ISBN :
0-7803-5207-6
Type :
conf
DOI :
10.1109/IGARSS.1999.773452
Filename :
773452
Link To Document :
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