An Effective Road Centerline Extraction Method From VHR

被引:3
|
作者
Lian, Renbao [1 ,2 ]
Zhang, Zhenmin [1 ,2 ]
Zou, Changzhong [3 ]
Huang, Liqin [4 ]
机构
[1] Fujian Jiangxia Univ, Coll Elect & Informat Sci, Fuzhou 350108, Peoples R China
[2] Fujian Jiangxia Univ, Smart Home Informat Collect & Proc Internet Thing, Fuzhou 350108, Peoples R China
[3] Fuzhou Univ, Coll Comp & Data Sci, Fuzhou 350108, Peoples R China
[4] Fuzhou Univ, Coll Phys & Informat Engn, Fuzhou 350108, Peoples R China
基金
中国国家自然科学基金;
关键词
Roads; Fitting; Kernel; Estimation; Manuals; Adaptation models; Surface fitting; Adaptive circular template; geodesic distance field (GDF); high-resolution remote sensing images; semiautomatic road centerline extraction; REMOTE-SENSING IMAGES;
D O I
10.1109/LGRS.2022.3170307
中图分类号
P3 [地球物理学]; P59 [地球化学];
学科分类号
0708 ; 070902 ;
摘要
Road digitizing is a labor-intensive task. For reducing labor cost, this letter presents an effective semiautomatic road delineation method based on geodesic distance field (GDF) and piecewise polygon fitting. The main components of the approach are optimal circle calculation, soft road center kernel density estimation (KDE), fast GDF generation, and piecewise polygon fitting model. First, the adaptive circular template is proposed to automatically measure the road width. Next, the soft road center kernel density is estimated for fast GDF generation, which supports the extraction of road centerline between two adjacent seeds. Finally, piecewise polygon fitting is used to refine the road centerline. Extensive experiments demonstrate that the proposed algorithm is efficient and robust in road delineation. The proposed approach takes almost the same time to extract any length of road segment given fixed image size, and no hyperparameters needs to be set.
引用
收藏
页数:5
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