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Sensors 2018, 18(1), 151; https://doi.org/10.3390/s18010151

Oil Spill Detection in Terma-Side-Looking Airborne Radar Images Using Image Features and Region Segmentation

1
Department of Physics, Systems Engineering and Signal Theory, University of Alicante, Alicante 03690, Spain
2
Computer Science Research Institute, University of Alicante, Alicante 03690, Spain
*
Author to whom correspondence should be addressed.
Received: 29 November 2017 / Revised: 30 December 2017 / Accepted: 4 January 2018 / Published: 8 January 2018
(This article belongs to the Special Issue Sensors for Oil Applications)
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Abstract

This work presents a method for oil-spill detection on Spanish coasts using aerial Side-Looking Airborne Radar (SLAR) images, which are captured using a Terma sensor. The proposed method uses grayscale image processing techniques to identify the dark spots that represent oil slicks on the sea. The approach is based on two steps. First, the noise regions caused by aircraft movements are detected and labeled in order to avoid the detection of false-positives. Second, a segmentation process guided by a map saliency technique is used to detect image regions that represent oil slicks. The results show that the proposed method is an improvement on the previous approaches for this task when employing SLAR images. View Full-Text
Keywords: maritime surveillance; oil spill detection; Side-Looking Airborne Radar; radar detection maritime surveillance; oil spill detection; Side-Looking Airborne Radar; radar 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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Gil, P.; Alacid, B. Oil Spill Detection in Terma-Side-Looking Airborne Radar Images Using Image Features and Region Segmentation. Sensors 2018, 18, 151.

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