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Airport Detection in SAR Images via Salient Line Segment Detector and Edge-Oriented Region Growing

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journal contribution
posted on 2020-11-20, 15:39 authored by J Tu, F Gao, J Sun, A Hussain, Huiyu Zhou
Airport detection in synthetic aperture radar (SAR) images has attracted much concern in the field of remote sensing. Affected by other salient objects with geometrical features similar to those of airports, traditional methods often generate false detections. In order to produce the geometrical features of airports and suppress the influence of irrelevant objects, we propose a novel method for airport detection in SAR images. Firstly, a salient line segment detector (SLSD) is constructed to extract salient line segments in the SAR images. Secondly, we obtain the airport support regions by grouping these line segments according to the commonality of these geometrical features. Finally, we design an edge-oriented region growing (EORG) algorithm, where growing seeds are selected from the airport support regions with the help of edge information in SAR images. Using EORG, the airport region can be mapped by performing region growing with these seeds. We implement experiments on real radar images to validate the effectiveness of our method. The experimental results demonstrate that our method can acquire more accurate locations and contours of airports than several state of the art airport detection algorithms.

Funding

10.13039/501100001809-National Natural Science Foundation of China;

History

Citation

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing

Author affiliation

Department of Informatics

Version

  • AM (Accepted Manuscript)

Published in

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing

Publisher

Institute of Electrical and Electronics Engineers

issn

1939-1404

Acceptance date

2020-11-03

Copyright date

2020

Available date

2020-11-06

Language

en

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