Data/hora: 01/06/2024 15:49:57

Provedor de dados: | 5
País: | France
Título: | Partially supervised oil-slick detection by SAR imagery using kernel expansion
Autores: | Mercier, Grégoire; Ardhuin, Fanny.
Data: | 2006-10
Ano: | 2006
Palavras-chave: | Water pollution; Synthetic aperture radar; Sea surface; Satellite applications; Oil spill; Image analysis.
Resumo: | Spaceborne synthetic aperture radar (SAR) is well adapted to detect ocean pollution independently from daily or weather conditions. In fact, oil slicks have a specific impact on ocean wave spectra. Initial wave spectra may be characterized by three kinds of waves, namely big, medium, and small, which correspond physically to gravity and gravity-capillary waves. The increase of viscosity, due to the presence of oil damps gravity-capillary waves. This induces not only a damping of the backscattering to the sensor but also a damping of the energy of the wave spectra. Thus, local segmentation of wave spectra may be achieved by the segmentation of a multiscale decomposition of the original SAR image. In this paper, a semisupervised oil-slick detection is proposed by using a kernel-based abnormal detection into the wavelet decomposition of a SAR image. It performs accurate detection with no consideration to signal stationarity nor to the presence of strong backscatters (such as a ship). The algorithm has been applied on ENVISAT Advanced SAR images. It yields accurate segmentation results even for small slicks, with a very limited number of false alarms.
Tipo: | Text
Idioma: | Inglês

Identificador:

http://archimer.ifremer.fr/doc/2006/publication-1948.pdf

DOI:10.1109/TGRS.2006.881078

Editor: | IEEE Geoscience and Remote Sensing Society
Relação: | http://archimer.ifremer.fr/doc/00000/1948/
Formato: | application/pdf
Fonte: | IEEE Transactions on Geoscience and Remote Sensing (0196-2892) (IEEE Geoscience and Remote Sensing Society), 2006-10 , Vol. 44 , N. 10 , P. 2839-2846
Fonte: | 2006 IEEE