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首页> 外文期刊>International journal of remote sensing >Building extraction from very high-resolution synthetic aperture radar images based on statistical and structural information fusion
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Building extraction from very high-resolution synthetic aperture radar images based on statistical and structural information fusion

机译：基于统计和结构信息融合的基于统计和结构信息融合的高分辨率合成孔径雷达图像建筑提取

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摘要

To investigate the limits of building detection from very high-resolution (VHR) synthetic aperture radar (SAR) images, a new method, based on statistical and structural information fusion, is proposed in this paper. The proposed method contains two stages: First, using order statistics constant false alarm rate (OS-CFAR) and power ratio (PR) detectors, a set of detections are made. These detections have different statistical properties, compared to the other objects, and these properties are selected for discriminating buildings from clutters. Second, the morphological analysis is used for increasing the precision of the detection. In this stage, segments, which have the most similarities to buildings in terms of shape and size, are extracted via various structural elements (SEs). The final result is obtained by fusing the two sets of detections. The experimental results on the four real VHR SAR images show that the proposed method has a high detection rate (DR) and low false alarm rate (FAR).
机译：为了研究来自非常高分辨率（VHR）合成孔径雷达（SAR）图像的建筑物检测的限制，本文提出了一种基于统计和结构信息融合的新方法。所提出的方法包含两个阶段：首先，使用订单统计常量误报率（OS-CFAR）和功率比（PR）检测器，进行一组检测。与其他目的相比，这些检测具有不同的统计性质，并且选择这些性质用于鉴别来自折叠的建筑物。其次，形态学分析用于增加检测的精度。在该阶段，通过各种结构元件（SES）提取具有与形状和尺寸的建筑物最常见的段。通过融合两组检测来获得最终结果。四个真实VHR SAR图像上的实验结果表明，该方法具有高检测率（DR）和低误报率（远）。

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  • 来源
    《International journal of remote sensing》 |2019年第18期|7113-7126|共14页
  • 作者

    Adelipour Sadjad; Ghassemian Hassan;

  • 作者单位

    Tarbiat Modares Univ Fac Elect & Comp Engn Image Proc & Informat Anal Lab Tehran Iran;

    Tarbiat Modares Univ Fac Elect & Comp Engn Image Proc & Informat Anal Lab Tehran Iran;

  • 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
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