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Remote Sens. 2016, 8(9), 751; doi:10.3390/rs8090751

Compact Polarimetric SAR Ship Detection with m-δ Decomposition Using Visual Attention Model

1
Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Beijing 100094, China
2
University of Chinese Academy of Science, Beijing 100049, China
3
Department of Electronic Engineering, School of Electronic and Optical Engineering, Nanjing University of Science and Technology, Nanjing 210094, China
*
Author to whom correspondence should be addressed.
Academic Editors: Zhong Lu, Xiaofeng Li and Prasad S. Thenkabail
Received: 29 June 2016 / Revised: 2 September 2016 / Accepted: 8 September 2016 / Published: 12 September 2016
View Full-Text   |   Download PDF [7506 KB, uploaded 12 September 2016]   |  

Abstract

A few previous studies have illustrated the potentials of compact polarimetric Synthetic Aperture Radar (CP SAR) in ship detection. In this paper, we design a ship detection algorithm of CP SAR from the perspective of computer vision. A ship detection algorithm using the pulsed cosine transform (PCT) visual attention model is proposed to suppress background clutter and highlight conspicuous ship targets. It is the first time that a visual attention model is introduced to CP SAR application. The proposed algorithm is a quick and complete framework for practical use. Polarimetric features—the relative phase δ and volume scattering component—are extracted from m-δ decomposition to eliminate false alarms and modify the PCT model. The constant false alarm rate (CFAR) algorithm based on lognormal distribution is adopted to detect ship targets, after a clutter distribution fitting procedure of the modified saliency map. The proposed method is then tested on three simulated circular-transmit-linear-receive (CTLR) mode images, which covering East Sea of China. Compared with the detection results of SPAN and the saliency map with only single-channel amplitude, the proposed method achieves the highest detection rates and the lowest misidentification rate and highest figure of merit, proving the effectiveness of polarimetric information of compact polarimetric SAR ship detection and the enhancement from the visual attention model. View Full-Text
Keywords: synthetic aperture radar; compact polarimetric; ship detection; visual attention model synthetic aperture radar; compact polarimetric; ship detection; visual attention model
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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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Xu, L.; Zhang, H.; Wang, C.; Zhang, B.; Tian, S. Compact Polarimetric SAR Ship Detection with m-δ Decomposition Using Visual Attention Model. Remote Sens. 2016, 8, 751.

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