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SAR Image Edge Detection via Directional Bhattacharyya Coefficient with Its Application on Image Segmentation

机译:方向Bhattacharyya系数的SAR图像边缘检测及其在图像分割中的应用

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摘要

In this paper, a novel edge detector for synthetic aperture radar (SAR) images is proposed by introducing theBhattacharyya coefficient (BC) combining with the rotated biwindow configuration. Based on the quantified input image,the BC is computed from two sample distribution histograms of local regions supported by the subwindows on theopposite sides of the pixel to be detected. With biwindows of different directions sliding through the image, multipledirectional Bhattacharyya coefficient matrices are obtained, which are utilized to extract the edge strength map (ESM),characterizing the intensity variation in SAR images. Sequent nonmaximum suppression and hysteresis thresholdingrefine the extracted ESM into thin edges. Experiment results show that the proposed edge detector can accurately extractedges. Moreover, the BC-based ESM can act as a good precursor to guide SAR image segmentation based on regionmerging.
机译:本文通过结合旋转双窗口结构引入\ r \ nBhattacharyya系数(BC),提出了一种新型的合成孔径雷达(SAR)图像边缘检测器。基于量化的输入图像,从要检测的像素的\ r \ n相对侧上的子窗口所支持的局部区域的两个样本分布直方图计算BC。通过不同方向的双窗口在图像中滑动,可以获得多个\ r \ n方向的Bhattacharyya系数矩阵,这些矩阵用于提取边缘强度图(ESM),表征SAR图像中的强度变化。随后的非最大抑制和滞后阈值\ r \ n将提取的ESM细化为细边。实验结果表明,所提出的边缘检测器可以准确提取\ r \边界。此外,基于BC的ESM可以作为指导基于区域融合的SAR图像分割的良好先驱。

著录项

  • 来源
    《Eleventh International Conference on Machine Vision》|2018年|1104107.1-1104107.8|共8页
  • 会议地点 0277-786X;1996-756X
  • 作者单位

    National Laboratory of Radar Signal Processing, Xidian University, Xi’an, China;

    National Laboratory of Radar Signal Processing, Xidian University, Xi’an, China;

    College of Computer and Information Science, Fujian Agriculture and Forestry University, Fuzhou, China;

    National Laboratory of Radar Signal Processing, Xidian University, Xi’an, China;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
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