DocumentCode :
1154552
Title :
Oil Spill Detection in Radarsat and Envisat SAR Images
Author :
Solberg, Anne H S ; Brekke, Camilla ; Husøy, Per Ove
Volume :
45
Issue :
3
fYear :
2007
fDate :
3/1/2007 12:00:00 AM
Firstpage :
746
Lastpage :
755
Abstract :
We present algorithms for automatic detection of oil spills in synthetic aperture radar (SAR) images. The algorithms consist of three main parts, namely: 1) detection of dark spots; 2) feature extraction from the dark spot candidates; and 3) classification of dark spots as oil spills or look-alikes. The algorithms have been trained on a large number of Radarsat and Envisat Advanced Synthetic Aperture Radar (ASAR) images. The performance of the algorithm is compared to manual and semiautomatic approaches in a benchmark study using 59 Radarsat and Envisat images. The algorithms can be considered to be a good alternative to manual inspection when large ocean areas are to be inspected
Keywords :
feature extraction; image classification; marine pollution; oil pollution; radar imaging; synthetic aperture radar; water pollution measurement; Envisat SAR images; Radarsat SAR images; automatic detection; dark spot classification; dark spot detection; feature extraction; ocean pollution; oil spill detection; synthetic aperture radar; Aircraft; Cleaning; Clustering algorithms; Feature extraction; Oceans; Petroleum; Pollution; Radar detection; Sea surface; Synthetic aperture radar; Classification; feature extraction; oil spill detection; 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.2006.887019
Filename :
4106067
Link To Document :
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