Oil Spill Detection in Radarsat and Envisat SAR Images
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....
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Veröffentlicht in: | IEEE transactions on geoscience and remote sensing 2007-03, Vol.45 (3), p.746-755 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | 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 |
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ISSN: | 0196-2892 1558-0644 |
DOI: | 10.1109/TGRS.2006.887019 |