Application of Polarimetric-SAR Decompositions on RADARSAT-2 Fine Quad-Pol Images to Enhance the Performances of Ships D
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Application of Polarimetric‑SAR Decompositions on RADARSAT‑2 Fine Quad‑Pol Images to Enhance the Performances of Ships Detection Algorithms Hichem Mahgoun1 · Nour Elhouda Chaffa2 · Mounira Ouarzeddine2 · Boularbah Souissi2 Received: 22 April 2020 / Revised: 10 September 2020 / Accepted: 26 October 2020 © Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract Remote sensing of vessels is an important tool for ship safety and security at sea. In this work, we are interested in improving ships detection using polarimetric Synthetic Aperture Radar (SAR). To develop the appropriate method, different processing techniques are applied on Pol-SAR images such as fusion and polarimetric decompositions and we use adaptive threshold detectors to assess the performances of the processing techniques. The data exploited in this work were acquired on a port area of the city of Vancouver by using RADARSAT-2 satellite. In this paper it is shown first that when exploiting single polarization, the HH channel provides the highest score of detection probability (PD) of 87.2% for a false alarm probability (PFA) of 0.05%, and this while using the cell averaging constant false alarm rate (CA-CFAR) detector. The result is obtained comparatively with other polarizations (HV, VV) and detection algorithms. Second, the fusion of polarimetric channels achieves its best performances with the CA-CFAR detector, comparatively with the two parameters (2P)-CFAR and generalized likelihood ratio test (GLRT). Third, we find that among the conventional polarimetric techniques, the singular value decomposition (SVD) combined with CA-CFAR detector gives the best results and achieves a detection probability of 91% for a false alarm of 0.05%. This result was obtained by comparing the performances of other combinations of decompositions (Pauli, Freeman, Yamaguchi), fusion and ships detection algorithms. In this paper, we obtain with the proposed approach an increase of 3.8% in detection probability for false alarm probability of 0.05%. Keywords Ship detection · CFAR · SVD · Freeman · Yamaguchi · PFA * Hichem Mahgoun [email protected] 1
Laboratory SETRAM, BT.61, Ecole Nationale Supérieure Maritime, 42415 Bou‑Ismail, Algeria
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Faculty of Electronics and Computer Science, Laboratory LTIR, BP 32 EL Alia, University of Science and Technology Houari Boumediene, 16111 Algiers, Algeria
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Sensing and Imaging
(2020) 21:56
1 Introduction The need for maritime security and protection of environment has increased during the past years. In this scenario, the synthetic aperture radar (SAR) is one of the most effective tools that can contribute to the safety and security thanks to its ability to obtain images regardless of light and weather conditions. It is also well known that SAR is more suited to detect ship targets on the sea surface based on their brightness. This characteristic has contributed to the development of algorithms aimed at detecting bright scattering points on a darker background. In th
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