4.7 Article

A Semi-Automatic Method for Road Centerline Extraction From VHR Images

期刊

IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
卷 11, 期 11, 页码 1856-1860

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/LGRS.2014.2312000

关键词

Kernel density estimation (KDE); geodesic method; mean shift; road extraction; semi-automatic; very high resolution (VHR) satellite images

资金

  1. National Natural Science Foundation of China [41201451, 40901214]
  2. Ministry of Science and Technology of China [2012BAJ15B04, 2012AA12A305]

向作者/读者索取更多资源

This letter presents a semi-automatic approach to delineating road networks from very high resolution satellite images. The proposed method consists of three main steps. First, the geodesic method is used to extract the initial road segments that link the road seed points prescribed in advance by users. Next, a road probability map is produced based on these coarse road segments and a further direct thresholding operation separates the image into two classes of surfaces: the road and nonroad classes. Using the road class image, a kernel density estimation map is generated, upon which the geodesic method is used once again to link the foregoing road seed points. Experiments demonstrate that this proposed method can extract smooth correct road centerlines.

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