DocumentCode :
1203211
Title :
A FARIMA-based technique for oil slick and low-wind areas discrimination in sea SAR imagery
Author :
Bertacca, Massimo ; Berizzi, Fabrizio ; Mese, Enzo Dalle
Author_Institution :
Dept. of Inf. Eng., Univ. of Pisa, Italy
Volume :
43
Issue :
11
fYear :
2005
Firstpage :
2484
Lastpage :
2493
Abstract :
This paper introduces a new analysis technique, using the fractionally integrated autoregressive-moving average (FARIMA) model, to distinguish between low-wind and oil slick areas in high-resolution sea synthetic aperture radar (SAR) imagery. The method deals with the estimation of the fractional differencing and autoregressive-moving average parameters of the mean radial power spectral density of sea SAR images. The algorithm is applied and validated on dark areas corresponding to oil slicks, oil spills, and low-wind sea surface anomalies in European Remote Sensing 1 and 2 Precision Images of the Mediterranean Sea, North Sea, and Atlantic Ocean.
Keywords :
oceanographic regions; oceanographic techniques; radar imaging; remote sensing by radar; synthetic aperture radar; Atlantic Ocean; European Remote Sensing; Mediterranean Sea; North Sea; autoregressive-moving average parameters; fractional differencing average parameter; fractionally integrated autoregressive-moving average; long-range dependence; low wind; oil slick; radial power spectral density; sea SAR imagery; sea surface anomaly; synthetic aperture radar; Amorphous materials; Brownian motion; Clutter; Fractals; Frequency; Image analysis; Petroleum; Remote sensing; Sea surface; Synthetic aperture radar; Fractionally integrated autoregressive-moving average (FARIMA) models; long-range dependence (LRD); oil slicks; synthetic aperture radar (SAR);
fLanguage :
English
Journal_Title :
Geoscience and Remote Sensing, IEEE Transactions on
Publisher :
ieee
ISSN :
0196-2892
Type :
jour
DOI :
10.1109/TGRS.2005.857622
Filename :
1522609
Link To Document :
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