Abstract
Algorithms based on SAR images for the purpose of detecting illegal oil spill pollution in the marine environment are studied. This paper focus on the feature extraction step, aiming at identifying features that lead to significant improvements in classification performance compared to earlier reported results. Both traditional region descriptors, features tailored to oil spill detection and techniques originally associated with other applications are evaluated. Experimental results show an increase from 89% to 97% in the number of suspected oil spills detected.
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Frate, F.D., Petrocchi, A., Lichtenegger, J., Calabresi, G.: Neural networks for oil spill detection using ERS-SAR data. IEEE Trans. on Geos. and Remote Sensing 38, 2282–2287 (2000)
Fiscella, B., Giancaspro, A., Nirchio, F., Pavese, P., Trivero, P.: Oil spill detection using marine SAR images. Int. J. of Remote Sensing 21, 3561–3566 (2000)
Solberg, A.H.S., Storvik, G., Solberg, R., Volden, E.: Automatic detection of oil spills in ERS SAR images. IEEE Trans. on Geos. and Remote Sensing 37, 1916–1924 (1999)
Solberg, A.H.S., Solberg, R.: A large-scale evaluation of features for automatic detection of oil spills in ERS SAR images. In: Proc. IGARSS 1996, May 27-31, vol. 3, pp. 1484–1486 (1996)
Topouzelis, K., Karathanassi, V., Pavlakis, P., Rokos, D.: Oil spill detection: SAR multi-scale segmentation & object features evaluation. In: Proc. SPIE. Remote sensing of the ocean and sea ice 2002, September 23-27, vol. 4880, pp. 77–87 (2003)
Solberg, A.H.S., Brekke, C., Solberg, R., Husøy, P.O.: Algorithms for oil spill detection in Radarsat and ENVISAT SAR images. In: Proc. IGARSS 2004, September 20-24, vol. 7, pp. 4909–4912 (2004)
Girard-Ardhuin, F., Mercier, G., Garello, R.: Oil slick detection by SAR imagery: potential and limitation. In: Proc. OCEANS 2003, vol. 1, pp. 164–169 (2003)
Nixon, M., Aguado, A.: Feature Extraction & Image Processing. Newnes (2002)
Lobregt, S., Viergever, M.A.: A discrete dynamic contour model. IEEE Trans. on Med. Imaging 14, 12–24 (1995)
Indregard, M., Solberg, A., Clayton, P.: D2-report on benchmarking oil spill recognition approaches and best practice. Technical report, Oceanides, EC, Archive No. 04-10225-A-Doc, Contr. No: EVK2-CT-2003-00177 (2004)
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Brekke, C., Solberg, A.H.S. (2005). Feature Extraction for Oil Spill Detection Based on SAR Images. In: Kalviainen, H., Parkkinen, J., Kaarna, A. (eds) Image Analysis. SCIA 2005. Lecture Notes in Computer Science, vol 3540. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11499145_9
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DOI: https://doi.org/10.1007/11499145_9
Publisher Name: Springer, Berlin, Heidelberg
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