Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/12818
Title: A road centerline extraction algorithm from high resolution satellite imagery
Authors: Miao, ZL
Shi, WZ 
Zhang, H
Keywords: High resolution satellite imagery
Multivariate adaptive regression splines
Road centerline extraction
Shape feature
Issue Date: 2013
Publisher: 该学报
Source: 中囯矿业大学学报 (Journal of China University of Mining & Technology), 2013, v. 42, no. 5, p. 887-892+898 How to cite?
Journal: 中囯矿业大学学报 (Journal of China University of Mining & Technology) 
Abstract: Traditional road extraction methods rarely consider the shape features and thus the extracted centerline is not smooth. To overcome the aforementioned limitations, a new road centerline extraction algorithm from high resolution satellite imagery using shape features and multivariate adaptive regression splines (MARS) is proposed in this paper. The method has three main steps. Firstly, an improved shape feature is developed to filter the segmentation result to extract linear features. The spectral information is then used to extract pure road segments from the linear features. Finally, road centerline is extracted using MARS. The proposed method is programmed by Matlab and tested on three high resolution imageries. The experimental results indicate that the improved shape feature can effectively extract linear features and the smoothness of road centerlines extracted by MARS is higher than that of traditional methods.
URI: http://hdl.handle.net/10397/12818
ISSN: 1000-1964
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