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A new shape descriptor for road network separation from parking lots and intersection detection on VHR remote sensing images

机译:一种新的形状描述符,用于远程遥感图像的停车场和交叉路口的道路网络分离

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摘要

One of the main problems in automating road network extraction from high-resolution satellite images is the misclassification between roads and other spectrally similar objects. Significant work is already done on the road class refinement direction. But, extraction of the roads that are closely adjacent to parking lots/buildings and identification of major road intersection is still an issue as they are misclassified. In this paper, a new shape descriptor to separate roads from spectrally similar non-road objects and to identify road network intersection is proposed. The proposed approach classified the input image into road and non-road classes using spectral features at first. In the binary image, considering roads continuous and elongated homogeneous regions, a new shape descriptor measuring the continuity of road pixels in a different direction is applied. The experiments on worldview-2, Ikonos, and GeoEye images showed that the proposed method is simple and effective in automating the separation of roads which are connected to parking lots/buildings and it can identify road intersection correctly.
机译:高分辨率卫星图像自动化道路网络提取的主要问题之一是道路和其他光谱相似的物体之间的错误分类。大量工作已经在道路课程方向上完成。但是,与停车场/建筑物密切相关的道路提取以及主要道路交叉路口的识别仍然是它们被错误分类的问题。在本文中,提出了一种新的形状描述符,以将来自光谱相似的非公路对象的道路分开并识别道路网络交叉路口。该方法首先使用光谱特征将输入图像分类为道路和非道路类。在二值图像中,考虑道路连续和细长的均匀区域,施加了一种新的形状描述符,测量在不同方向上的道路像素的连续性。在WorldView-2,Ikonos和Geoeye图像上的实验表明,建议的方法在自动化连接到停车场/建筑物的道路上的自动化方面简单有效,它可以正确识别道路交叉路口。

著录项

  • 来源
    《International journal of remote sensing》 |2020年第12期|4226-4237|共12页
  • 作者

    Mostafa Yasser;

  • 作者单位

    Sohag Univ Civil Engn Dept Fac Engn Sohag Egypt;

  • 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

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