| Registro completo |
| Provedor de dados: |
ArchiMer
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| País: |
France
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| Título: |
Partially supervised oil-slick detection by SAR imagery using kernel expansion
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| Autores: |
Mercier, Grégoire
Ardhuin, Fanny
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| Data: |
2006-10
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| Ano: |
2006
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| Palavras-chave: |
Water pollution
Synthetic aperture radar
Sea surface
Satellite applications
Oil spill
Image analysis
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| 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.
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| Tipo: |
Text
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| Idioma: |
Inglês
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| Identificador: |
http://archimer.ifremer.fr/doc/2006/publication-1948.pdf
DOI:10.1109/TGRS.2006.881078
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| Editor: |
IEEE Geoscience and Remote Sensing Society
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| Relação: |
http://archimer.ifremer.fr/doc/00000/1948/
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| Formato: |
application/pdf
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| 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
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| Direitos: |
2006 IEEE
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