Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/22066
Title: A semi-automatic method for road centerline extraction from VHR images
Authors: Miao, Z
Wang, B
Shi, W 
Zhang, H
Keywords: Geodesic method
Kernel density estimation (KDE)
Mean shift
Road extraction
Semi-automatic
Very high resolution (VHR) satellite images
Issue Date: 2014
Publisher: Institute of Electrical and Electronics Engineers
Source: IEEE geoscience and remote sensing letters, 2014, v. 11, no. 11, 6784347, p. 1856-1860 How to cite?
Journal: IEEE geoscience and remote sensing letters 
Abstract: 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.
URI: http://hdl.handle.net/10397/22066
ISSN: 1545-598X
DOI: 10.1109/LGRS.2014.2312000
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