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Anisotropic diffusion for speckle filtering of polarimetric synthetic aperture radar imagery

机译:各向异性扩散用于极化合成孔径雷达图像的斑点滤波

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摘要

The mission of speckle filtering is more intricate for a polarimetric synthetic aperture radar (SAR) system than for a single polarization SAR system. A new speckle filter that employs nonlinear anisotropic diffusion is proposed. The speckle filtering principles in a polarimetric SAR system are thoroughly investigated. Our study demonstrates that preservation of polarimetric properties and reduction of speckle level are very important clauses among those principles. Anisotropic diffusion outperforms window-based filters because it utilizes a diffusion tensor that can bias the direction of diffusion toward the orientation of interesting features. The procedure of diffusion is iterative, so it can lead to a gradual alleviation of speckle noise. The parameters for diffusion are flexible and adjustable, thus the filtering results are controllable according to the requirements of specific applications. Multidimensional and vector-valued model is combined with local statistics based on polarimetric SAR configuration. The experimental results on electromagnetics institute synthetic aperture radar (EMISA R) datasets show that the proposed filter has good performance in speckle reduction and preservation of polarimetric properties.
机译:与单极化SAR系统相比,极化合成孔径雷达(SAR)系统的斑点滤波任务更为复杂。提出了一种新的利用非线性各向异性扩散的散斑滤波器。对极化SAR系统中的斑点滤波原理进行了深入研究。我们的研究表明,保留偏振特性和降低斑点水平是这些原则中非常重要的条款。各向异性扩散优于基于窗口的滤镜,因为它利用了扩散张量,可以将扩散方向偏向有趣特征的方向。扩散的过程是迭代的,因此可以逐步减轻斑点噪声。扩散参数灵活可调,因此过滤结果可根据具体应用要求进行控制。多维矢量值模型与基于极化SAR配置的本地统计信息相结合。在电磁学机构合成孔径雷达(EMISA R)数据集上的实验结果表明,该滤波器在减少斑点和保持偏振特性方面具有良好的性能。

著录项

  • 来源
    《Journal of electronic imaging》 |2013年第1期|013003.1-013003.7|共7页
  • 作者单位

    Huazhong University of Science and Technology Institute for Pattern Recognition and Artificial Intelligence Wuhan 430074, China and Guangdong University of Technology School of Computer Science Guangzhou 510006, China;

    Huazhong University of Science and Technology Institute for Pattern Recognition and Artificial Intelligence Wuhan 430074, China;

    Guangdong University of Technology School of Computer Science Guangzhou 510006, China;

    Guangdong University of Technology School of Information Engineering Guangzhou 510006, China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

  • 入库时间 2022-08-18 01:17:34

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