Vol.:(0123456789)
Sensing and Imaging (2020) 21:56
https://doi.org/10.1007/s11220-020-00321-3
1 3
ORIGINAL PAPER
Application of Polarimetric‑SAR Decompositions
on RADARSAT‑2 Fine Quad‑Pol Images to Enhance
the Performances of Ships Detection Algorithms
Hichem Mahgoun
1
· Nour Elhouda Chafa
2
· Mounira Ouarzeddine
2
·
Boularbah Souissi
2
Received: 22 April 2020 / Revised: 10 September 2020 / Accepted: 26 October 2020 /
Published online: 6 November 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 Syn-
thetic Aperture Radar (SAR). To develop the appropriate method, diferent pro-
cessing 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 frst that when exploiting single polarization, the HH channel provides
the highest score of detection probability (PD) of 87.2% for a false alarm proba-
bility (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 polariza-
tions (HV, VV) and detection algorithms. Second, the fusion of polarimetric chan-
nels achieves its best performances with the CA-CFAR detector, comparatively with
the two parameters (2P)-CFAR and generalized likelihood ratio test (GLRT). Third,
we fnd 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
mahgoun@live.fr
1
Laboratory SETRAM, BT.61, Ecole Nationale Supérieure Maritime, 42415 Bou-Ismail, Algeria
2
Faculty of Electronics and Computer Science, Laboratory LTIR, BP 32 EL Alia, University
of Science and Technology Houari Boumediene, 16111 Algiers, Algeria