A Gram-Schmidt Transformation-based Hierarchical Urban Road Centerline Extraction Method

Lipeng Gao, Sitong Sun, Fei Wang, Jun Zhu, Peng Luo
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Abstract

This paper proposed a novel approach for extracting road centerlines in the urban area. The proposed approach consists of three main blocks: (1) DSM data are added to the available high resolution remote sensing images (HRRSI) and the two types of data are fused by the Gram-Schmidt transformation; (2) A hierarchical road extraction method is proposed to extract the road centerlines. (3) Finally, an improved road trimming (IRT) algorithm is implemented for road centerline refining. Experimental results on four datasets show that the proposed method obtains competitively satisfactory results.
基于Gram-Schmidt变换的分层城市道路中心线提取方法
提出了一种提取城市道路中心线的新方法。该方法包括三个主要部分:(1)将DSM数据添加到现有的高分辨率遥感图像(HRRSI)中,并通过Gram-Schmidt变换将两类数据融合;(2)提出了分层道路提取方法,提取道路中心线。(3)最后,实现了一种改进的道路切边(IRT)算法,用于道路中心线的细化。在四个数据集上的实验结果表明,该方法获得了相当满意的结果。
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