Paper Info
Title
Method Based on Edge Constraint and Fast Marching for Road Centerline Extraction from Very High-Resolution Remote Sensing Images.
Abstract
In recent decades, road extraction from very high-resolution (VHR) remote sensing images has become popular and has attracted extensive research efforts. However, the very high spatial resolution, complex urban structure, and contextual background effect of road images complicate the process of road extraction. For example, shadows, vehicles, or other objects may occlude a road located in a developed urban area. To address the problem of occlusion, this study proposes a semiautomatic approach for road extraction from VHR remote sensing images. First, guided image filtering is employed to reduce the negative effects of nonroad pixels while preserving edge smoothness. Then, an edge-constraint-based weighted fusion model is adopted to trace and refine the road centerline. An edge-constraint fast marching method, which sequentially links discrete seed points, is presented to maintain road-point connectivity. Six experiments with eight VHR remote sensing images (spatial resolution of 0.3 m/pixel to 2 m/pixel) are conducted to evaluate the efficiency and robustness of the proposed approach. Compared with state-of-the-art methods, the proposed approach presents superior extraction quality, time consumption, and seed-point requirements.
Year
DOI
Venue
2018
10.3390/rs10060900
REMOTE SENSING
Keywords
Field
DocType
road extraction,very high-resolution image,fast marching method,semiautomatic,edge constraint
Computer vision,Fast marching method,Remote sensing,Filter (signal processing),Robustness (computer science),Pixel,Artificial intelligence,Geology,Smoothness,Image resolution,Urban structure
Journal
Volume
Issue
Citations 
10
6
3
PageRank 
References 
Authors
0.45
20
4
Name
Order
Citations
PageRank
Lipeng Gao130.79
Wenzhong Shi277886.23
Zelang Miao312513.82
Zhi-yong Lv44711.83