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Speckle suppression in synthetic aperture radar ocean internal solitary wave images with curvelet transform

机译:Curvelet变换抑制合成孔径雷达海洋内孤立波图像中的斑点

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摘要

This paper proposes a speckle-suppression method for ocean internal solitary wave (ISW) synthetic aperture radar (SAR) images by using the curvelet transform. The band-shaped signatures of ocean ISWs in SAR images show obvious scale and directional characteristics. The curvelet transform possesses a very high scale and directional sensitivity. Therefore, the curvelet transform is very efficient in analyzing wave signals in SAR images. A noisy ocean ISW SAR image can be decomposed at different scales, directions, and positions using the curvelet transform. The information of the ISWs is centralized in the curvelet coefficients of certain directions under certain scales, whereas the speckle noise is distributed in every scale and direction. By manipulating the curvelet coefficients, the signals of the ISWs can be extracted from the noisy SAR image. Finally, the speckle noise is suppressed and the ISW feature is enhanced by adding the signals of the ISWs back to the original SAR image. Experiments demonstrate the effectiveness of this method.
机译:提出了一种利用curvelet变换对海洋内部孤立波(ISW)合成孔径雷达(SAR)图像进行散斑抑制的方法。 SAR图像中海洋ISW的带状特征表现出明显的尺度和方向特征。 Curvelet变换具有很高的比例和方向敏感性。因此,曲线波变换在分析SAR图像中的波信号时非常有效。可以使用Curvelet变换在不同的比例,方向和位置上分解嘈杂的海洋ISW SAR图像。 ISW的信息集中在特定比例下特定方向的Curvelet系数中,而斑点噪声则分布在每个比例和方向上。通过操纵Curvelet系数,可以从嘈杂的SAR图像中提取ISW的信号。最后,通过将ISW的信号添加回原始SAR图像,可以抑制斑点噪声并增强ISW功能。实验证明了该方法的有效性。

著录项

  • 来源
    《海洋学报(英文版)》 |2016年第9期|13-21|共9页
  • 作者单位

    College of 0ceanic and Atmospheric Sciences, 0cean University of China, Qingdao 266100, China;

    State Key Laboratory of Tropical 0ceanography, South China Sea Institute of 0ceanology, Chinese Academy of Sciences, Guangzhou 510301, China;

    College of 0ceanic and Atmospheric Sciences, 0cean University of China, Qingdao 266100, China;

    College of 0ceanic and Atmospheric Sciences, 0cean University of China, Qingdao 266100, China;

    0cean Remote Sensing Institute, 0cean University of China, Qingdao 266100, China;

  • 收录信息 中国科学引文数据库(CSCD);中国科技论文与引文数据库(CSTPCD);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

  • 入库时间 2022-08-19 03:57:52
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