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Ship Target Automatic Detection Based on Hypercomplex Flourier Transform Saliency Model in High Spatial Resolution Remote-Sensing Images
J. He,Y. F. Guo and H. F. Yuan
2020
发表期刊Sensors
卷号20期号:9页码:15
摘要Efficient ship detection is essential to the strategies of commerce and military. However, traditional ship detection methods have low detection efficiency and poor reliability due to uncertain conditions of the sea surface, such as the atmosphere, illumination, clouds and islands. Hence, in this study, a novel ship target automatic detection system based on a modified hypercomplex Flourier transform (MHFT) saliency model is proposed for spatial resolution of remote-sensing images. The method first utilizes visual saliency theory to effectively suppress sea surface interference. Then we use OTSU methods to extract regions of interest. After obtaining the candidate ship target regions, we get the candidate target using a method of ship target recognition based on ResNet framework. This method has better accuracy and better performance for the recognition of ship targets than other methods. The experimental results show that the proposed method not only accurately and effectively recognizes ship targets, but also is suitable for spatial resolution of remote-sensing images with complex backgrounds.
DOI10.3390/s20092536
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收录类别SCI ; EI
语种英语
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文献类型期刊论文
条目标识符http://ir.ciomp.ac.cn/handle/181722/64879
专题中国科学院长春光学精密机械与物理研究所
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J. He,Y. F. Guo and H. F. Yuan. Ship Target Automatic Detection Based on Hypercomplex Flourier Transform Saliency Model in High Spatial Resolution Remote-Sensing Images[J]. Sensors,2020,20(9):15.
APA J. He,Y. F. Guo and H. F. Yuan.(2020).Ship Target Automatic Detection Based on Hypercomplex Flourier Transform Saliency Model in High Spatial Resolution Remote-Sensing Images.Sensors,20(9),15.
MLA J. He,Y. F. Guo and H. F. Yuan."Ship Target Automatic Detection Based on Hypercomplex Flourier Transform Saliency Model in High Spatial Resolution Remote-Sensing Images".Sensors 20.9(2020):15.
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