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Hardware-accelerated edge detection for polarimetric synthetic aperture radar data

Nguyen, Quang Huy and Lee, Ken Yoong and Aung, Myo Tun and Bretschneider, Timo and McLoughlin, Ian Vince (2009) Hardware-accelerated edge detection for polarimetric synthetic aperture radar data. In: 2009 IEEE International Geoscience and Remote Sensing Symposium. IEEE. ISBN 978-1-4244-3394-0. E-ISBN 978-1-4244-3395-7. (doi:10.1109/IGARSS.2009.5417338) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:48888)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided.
Official URL:
http://dx.doi.org/10.1109/IGARSS.2009.5417338

Abstract

From the literature review, there are two constant false alarm rate detectors for detecting edges in multi-look fully polarimetric synthetic aperture radar (POLSAR) imagery, namely the likelihood ratio edge detector and the Roy's largest eigenvalue-based edge detector. In the latter approach, one major restriction is the computation complexity, i.e. in the context of the chosen C language-based implementation. Thus, in this paper, a novel hardware-based architecture is presented to improve the processing time for the Roy's largest eigenvalue-based edge detection. The algorithm was implemented in a field-programmable gate array (FPGA) with an accelerated solution targeting data rates of up to 1 Gb/s. Its performance was examined using nine-look NASA/JPL C-band data and evaluated in terms of processing speed and accuracy as compared to the C language-based implementation on a personal computer (PC) with a Core¿ 2 Duo processor clocked at 2.2 GHz.

Item Type: Book section
DOI/Identification number: 10.1109/IGARSS.2009.5417338
Uncontrolled keywords: real-time system, Roy's largest eigenvalue, edge detection, field programmable gate arrays, floating point, NASA
Subjects: T Technology
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing
Depositing User: Ian McLoughlin
Date Deposited: 07 Sep 2015 15:08 UTC
Last Modified: 16 Nov 2021 10:19 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/48888 (The current URI for this page, for reference purposes)

University of Kent Author Information

McLoughlin, Ian Vince.

Creator's ORCID: https://orcid.org/0000-0001-7111-2008
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