首页> 中文期刊> 《交通运输工程学报(英文版)》 >A review of road extraction from remote sensing images

A review of road extraction from remote sensing images

         

摘要

As a significant role for traffic management, city planning, road monitoring, GPS navigation and map updating, the technology of road extraction from a remote sensing (RS) image has been a hot research topic in recent years. In this paper, after analyzing different road features and road models, the road extraction methods were classified into the classifi-cation-based methods, knowledge-based methods, mathematical morphology, active contour model, and dynamic programming. Firstly, the road features, road model, existing difficulties and interference factors for road extraction were analyzed. Secondly, the principle of road extraction, the advantages and disadvantages of various methods and research achievements were briefly highlighted. Then, the comparisons of the different road extraction algorithms were performed, including road features, test samples and shortcomings. Finally, the research results in recent years were summarized emphatically. It is obvious that only using one kind of road features is hard to get an excellent extraction effect. Hence, in order to get good results, the road extraction should combine multiple methods according to the real applications. In the future, how to realize the complete road extraction from a RS image is still an essential but challenging and important research topic.

著录项

  • 来源
    《交通运输工程学报(英文版)》 |2016年第3期|271-282|共12页
  • 作者单位

    School of Information Engineering, Chang'an University, Xi'an 710064, China;

    Royal Institute of Technology, Stockholm, Sweden;

    School of Information Engineering, Chang'an University, Xi'an 710064, China;

    School of Information Engineering, Chang'an University, Xi'an 710064, China;

    School of Information Engineering, Chang'an University, Xi'an 710064, China;

    School of Information Engineering, Chang'an University, Xi'an 710064, China;

    Department of Computer Science and Technology, Umeu University, Umeu, Sweden;

  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号