The recognition of wakes generated by dark vessels is a tremendous and interesting challenge in the field of maritime surveillance by Synthetic Aperture Radar (SAR) images. The paper aims at assessing the detection performance in different scenarios by processing Sentinel-1 SAR images along with ground truth data. Results confirm that the Radon-based approach is an effective technique for wake-based detection of dark vessels, and they lead to a deeper understanding of the effects of different sea and wind conditions. In general, the best applicative scenario is a marine image characterized by homogeneous sea clutter; the presence of natural surface film or strong transition from low wind speed areas to more windy zones worsen the detection performance. Nonetheless, the proposed approach features dark vessel detection capabilities by identifying their wakes, without any a priori knowledge of their positions

Towards Automatic Recognition of Wakes Generated by Dark Vessels in Sentinel-1 Images / Graziano, Maria Daniela; Renga, Alfredo. - In: REMOTE SENSING. - ISSN 2072-4292. - 13:10(2021). [10.3390/rs13101955]

Towards Automatic Recognition of Wakes Generated by Dark Vessels in Sentinel-1 Images

Graziano, Maria Daniela;Renga, Alfredo
2021

Abstract

The recognition of wakes generated by dark vessels is a tremendous and interesting challenge in the field of maritime surveillance by Synthetic Aperture Radar (SAR) images. The paper aims at assessing the detection performance in different scenarios by processing Sentinel-1 SAR images along with ground truth data. Results confirm that the Radon-based approach is an effective technique for wake-based detection of dark vessels, and they lead to a deeper understanding of the effects of different sea and wind conditions. In general, the best applicative scenario is a marine image characterized by homogeneous sea clutter; the presence of natural surface film or strong transition from low wind speed areas to more windy zones worsen the detection performance. Nonetheless, the proposed approach features dark vessel detection capabilities by identifying their wakes, without any a priori knowledge of their positions
2021
Towards Automatic Recognition of Wakes Generated by Dark Vessels in Sentinel-1 Images / Graziano, Maria Daniela; Renga, Alfredo. - In: REMOTE SENSING. - ISSN 2072-4292. - 13:10(2021). [10.3390/rs13101955]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11588/852824
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