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Ships as salient objects in Synthetic Aperture Radar imagery
Citation
Schwegmann, CP and Kleynhans, W and Salmon, BP and Mdakane, LW and Meyer, RGV, Ships as salient objects in Synthetic Aperture Radar imagery, Proceedings of 2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 10-15 July 2016, Beijing, China, pp. 6898-6901. ISBN 978-1-5090-3332-4 (2016) [Non Refereed Conference Paper]
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DOI: doi:10.1109/IGARSS.2016.7730800
Abstract
The widespread access to Synthetic Aperture Radar data has created a need for more precise ship extraction, specifically in low-to-medium resolution imagery. While Synthetic Aperture Radar pixel resolution is improving for a large swaths, information about ships from within the Synthetic Aperture Radar intensity imagery is still sparse. Ships that are a few pixels across provide little information for classification and even less when improperly extracted. This paper presents a novel perspective on ships in Synthetic Aperture Radar imagery by viewing them as visually salient objects. The paper introduces common methods of ship object extraction and demonstrates how salient object mapping can improve the accuracy of extracted ships in Synthetic Aperture Radar imagery, providing better representation of ship objects. The Frequency-tuned and Spectral Residual Saliency Maps methods were tested against a unique dataset with ground truth information and were shown to have the best performance amongst all the conventional methods tested using six performance metrics.
Item Details
Item Type: | Non Refereed Conference Paper |
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Keywords: | synthetic aperture radar, object detection, marine technology |
Research Division: | Engineering |
Research Group: | Communications engineering |
Research Field: | Signal processing |
Objective Division: | Expanding Knowledge |
Objective Group: | Expanding knowledge |
Objective Field: | Expanding knowledge in engineering |
UTAS Author: | Salmon, BP (Dr Brian Salmon) |
ID Code: | 117095 |
Year Published: | 2016 |
Web of Science® Times Cited: | 1 |
Deposited By: | Engineering |
Deposited On: | 2017-05-31 |
Last Modified: | 2017-05-31 |
Downloads: | 0 |
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