Road network detection by mathematical morphology
Road network detection by mathematical morphology
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DOI：
10.3929/ethz-a-004334280
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发表时间：
1999
期刊：
影响因子：
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通讯作者：
Chunsun Zhang;S. Murai;E. Baltsavias
中科院分区：
文献类型：
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作者：
Chunsun Zhang;S. Murai;E. Baltsavias
提出了一种从数字图像实现自动道路网络检测的方法。该方法基于数学形态学分析，而大多数道路提取算法基于线性分析方法。随着图像分辨率的增加，道路网络看起来是具有一定宽度的区域而不是细线。本文提出的方法首先对图像进行分类以找到道路网络区域，然后采用形态学平凡开放来避免包含与路面具有相似光谱特征的对象的噪声。所开发的方法已在高分辨率模拟图像和航空照片上进行了测试。结果表明，数学形态学为自动路网检测提供了有效的工具。
An approach to achieve automated road network detection from digital images is presented. The method is based on mathematical morphology analysis while most road extraction algorithms are based on linear analysis methods. As the image resolution increases, road networks appear to be areas with certain width rather than thin lines. The approach proposed in this paper firstly classifies the image to find road network regions, and then morphological trivial opening is adopted to avoid noise including objects that have similar spectral characteristics as road surfaces. The developed method has been tested on high resolution simulation images and aerial photos. The result shows that mathematical morphology provides an effective tool for automated road network detection.