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Remote Sens. 2017, 9(11), 1107;

Performance Analysis of Ship Wake Detection on Sentinel-1 SAR Images

Department of Industrial Engineering, University of Naples “Federico II”, Piazzale Tecchio, 80, 80125 Naples, Italy
Department of Industrial and Information Engineering, University of Campania “Luigi Vanvitelli”, Via Roma, 29, 81031 Aversa (CE), Italy
Author to whom correspondence should be addressed.
Received: 27 September 2017 / Revised: 26 October 2017 / Accepted: 27 October 2017 / Published: 30 October 2017
(This article belongs to the Special Issue Instruments and Methods for Ocean Observation and Monitoring)
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A novel technique for ship wake detection has been recently proposed and applied on X-band Synthetic Aperture Radar images provided by COSMO/SkyMed and TerraSAR-X. The approach shows that the vast majority of wake features are correctly detected and validated in critical situations. In this paper, the algorithm was applied to 28 wakes imaged by Sentinel-1 mission with different polarizations and incidence angles with the aim of testing the method’s robustness with reference to radar frequency and resolution. The detection process is properly modified. The results show that the features were correctly classified in 78.5% of cases, whereas false confirmations occur mainly on Kelvin cusps. Finally, the results were compared with the algorithm performance on X-band images, showing that no significant difference arises. In fact, the total false confirmations rate was 15.8% on X-band images and 18.5% on C-band images. Moreover, since the main criticality concerns again the false confirmation of Kelvin cusps, the same empirical criterion suggested for the X-band SAR images yielded a negligible 1.5% of false detection rate. View Full-Text
Keywords: Radon Transform; SAR images; Sentinel-1; ship wake detection Radon Transform; SAR images; Sentinel-1; ship wake detection

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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Graziano, M.D.; Grasso, M.; D’Errico, M. Performance Analysis of Ship Wake Detection on Sentinel-1 SAR Images. Remote Sens. 2017, 9, 1107.

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