Joint Enhancing Filtering for Road Network Extraction

被引:37
|
作者
Zang, Yu [1 ]
Wang, Cheng [1 ]
Yu, Yao [1 ]
Luo, Lun [2 ]
Yang, Ke [2 ]
Li, Jonathan [1 ,3 ]
机构
[1] Xiamen Univ, Fujian Key Lab Sensing & Comp Smart Cities, Xiamen 361005, Peoples R China
[2] China Transport Telecommun & Informat Ctr, Beijing 100011, Peoples R China
[3] Univ Waterloo, Dept Geog & Environm Management, Waterloo, ON N2L 3G1, Canada
来源
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING | 2017年 / 55卷 / 03期
关键词
Guided image filtering; joint enhancing filtering; road network extraction; IMAGE; TRACKING; AERIAL;
D O I
10.1109/TGRS.2016.2626378
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
In this paper, we propose a task-oriented enhancing technique for extracting road networks from satellite images. By exploiting an approximate estimation of the potential road edges for guidance, we developed a joint enhancing filtering framework to generate a version of the input image that facilitates road network extraction. First, an adaptive smoothing scheme is designed to suppress the interference of noise or heavy textures, such as residential areas or terrain boundaries. By combining this scheme with the proposed novel anisotropic shock filter, the edges of the potential road regions can be kept sharp and clear. Through abundant experimental comparisons with state-of-theart filtering techniques and quantitative evaluations using data from various satellite sensors, the performance of the proposed approach is comprehensively evaluated. The experimental results demonstrate that our system can address heavy high contrast textures and provide a meaningful improvement in the feature detection for road extraction.
引用
收藏
页码:1511 / 1525
页数:15
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