Fractal dimension algorithm for detecting oil spills using RADARSAT-1 SAR

Authors:
Maged Marghany;Mazlan Hashim;Arthur P. Cracknell
Affiliations:
Department of Remote Sensing, Faculty of Geoinformation Science and Engineering, Universiti Teknologi Malaysia, Skudai, Johore Bahru, Malaysia;Department of Remote Sensing, Faculty of Geoinformation Science and Engineering, Universiti Teknologi Malaysia, Skudai, Johore Bahru, Malaysia;Department of Remote Sensing, Faculty of Geoinformation Science and Engineering, Universiti Teknologi Malaysia, Skudai, Johore Bahru, Malaysia
Venue:
ICCSA'07 Proceedings of the 2007 international conference on Computational science and its applications - Volume Part I
Year:
2007

Citing 1
Cited 1

Introduction to statistical pattern recognition (2nd ed.)

Introduction to statistical pattern recognition (2nd ed.)

Comparative algorithms for oil spill detection from multi mode RADARSAT-1 SAR satellite data

ICCSA'11 Proceedings of the 2011 international conference on Computational science and its applications - Volume Part II

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Abstract

This paper introduces a method for modification of the formula of the fractal box counting dimension. The method is based on the utilization of the probability distribution formula in the fractal box count. The purpose of this method is to use it for the discrimination of oil spill areas from the surrounding features e.g., sea surface and look-alikes in RADARSAT-1 SAR data. The result shows that the new formula of the fractal box counting dimension is able to discriminate between oil spills and look-alike areas. The low wind area has the highest fractal dimension peak of 2.9, as compared to the oil slick and the surrounding rough sea. The maximum error standard deviation of low wind area is 0.68 which performs with fractal dimension value of 2.9.