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Remote Sensing Technology and Application
    
A New Ship Target Detection Algorithm based on SVMin High Resolution SAR Images
Xiong Wei,Xu Yongli,Yao Libo,Cui Yaqi
(Institute of Information Fusion,Naval Aeronautical and Astronautical University,Yantai 264001,China)
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Abstract  The characteristics of ocean background and target in the high resolution synthetic aperture radar (SAR) images are analyzed.Aiming at the requirements of ship detection in high-resolution synthetic aperture radar (SAR) image,the detection accuracy,intelligence level,real-time and processing efficiency,we put forward a high resolution SAR images ship detection algorithm based on support vector machine.The algorithm designs a pre-training support vector machine (SVM) classifier and complete the screening of the ship target block area,then the algorithm of optimal entropy thresholds proposed by Kapur,Sahoo,Wong(KSW) will be used on the target area selected for fine detection of ship targets.In this paper,several commercial satellite data,such as TerraSAR-X,are used to verify the experiment.Comparing with the classical CFAR detection algorithm,Experimental results show that the algorithm can improve the false alarm caused by the speckle noise and ocean clutter background inhomogeneity.At the same time,the detection speed is also increased by 20% to 35%.
Key words:  Synthetic Aperture Radar(SAR);Ship target detection;Support Vector Machine(SVM);KSW       fast algorithm     
Received:  19 December 2016      Published:  16 March 2018
TP 75  
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Xiong Wei
Xu Yongli
Yao Libo
Cui Yaqi

Cite this article: 

Xiong Wei,Xu Yongli,Yao Libo,Cui Yaqi. A New Ship Target Detection Algorithm based on SVMin High Resolution SAR Images. Remote Sensing Technology and Application, 2018, 33(1): 119-127.

URL: 

http://www.rsta.ac.cn/EN/10.11873/j.issn.1004-0323.2018.1.0119     OR     http://www.rsta.ac.cn/EN/Y2018/V33/I1/119

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