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
类别
资金
- National Natural Science Foundation of China [41201451, 40901214]
- Ministry of Science and Technology of China [2012BAJ15B04, 2012AA12A305]
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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