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A method for coastal oil tank detection in polarimetric SAR images based on recognition of T-shaped harbor

机译:基于T形港口识别的极化SAR图像中沿海油箱检测方法

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摘要

To automatically detect oil tanks in polarimetric syn-thetic aperture radar (SAR) images, a coastal oil tank detection method is proposed based on recognition of T-shaped harbor. First of all, the T-shaped harbor is detected to locate the region of inter-est (ROI) of oil tanks. Then all suspicious targets in the ROI are extracted by the segmentation of strong scattering targets and the classifier of H/α . The template targets are selected from the sus-picious targets by the combination of a proposed circular degree parameter and the similarity parameter (SP) of the polarimetric coherency matrix. Finally, oil tanks are detected according to the statistics of the similarity parameter between each suspicious tar-get and template targets in ROI. Polarimetric SAR data acquired by RADARSAT-2 over Berkeley and Singapore areas are used for testing. Experiment results show that most of the targets are correctly detected and the overall detection rate is close to 80%. The false rate is effectively reduced by the proposed algorithm compared with the method without T-shaped harbor recognition.
机译:为了自动检测极化合成孔径雷达(SAR)图像中的油箱,提出了一种基于T形港口识别的沿海油箱检测方法。首先,检测到T形港口以定位油箱的兴趣区域(ROI)。然后通过强散射目标的分割和H /α分类器提取ROI中的所有可疑目标。通过提议的圆度参数和极化相干矩阵的相似性参数(SP)的组合,从可疑目标中选择模板目标。最终,根据每个可疑目标和ROI中模板目标之间相似性参数的统计信息来检测油箱。 RADARSAT-2在伯克利和新加坡地区获得的极化SAR数据用于测试。实验结果表明,大多数目标都能被正确检测,总体检测率接近80%。与没有T形港口识别的方法相比,该算法有效地降低了错误率。

著录项

  • 来源
    《系统工程与电子技术(英文版)》 |2018年第3期|499-509|共11页
  • 作者单位

    Department of Electronic Engineering, Tsinghua University, Beijing 100084, China;

    National Satellite Ocean Application Service, Beijing 100081, China;

    Department of Electronic Engineering, Tsinghua University, Beijing 100084, China;

    Department of Geography, University of California Los Angeles, Los Angeles CA 90024, United States;

    Department of Electronic Engineering, Tsinghua University, Beijing 100084, China;

  • 收录信息 中国科学引文数据库(CSCD);
  • 原文格式 PDF
  • 正文语种 eng
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