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遥感技术与应用  2009, Vol. 24 Issue (3): 284-290    DOI: 10.11873/j.issn.1004-0323.2009.3.284
综述     
遥感图像道路信息提取方法研究进展
王培法1,王丽1,冯学智2,肖鹏峰2
(1. 南京信息工程大学遥感学院|江苏 南京〓210044;
2.南京大学地理信息科学系|江苏 南京〓210093)
Review of Road Extraction from Remote Sensing Images
WANG Pei-fa1,WANG Li1,FENG Xue-zhi2,XIAO Peng-feng2
 (1.School of Remote Sensing,Nanjing University of Information Science &|Technology,Nanjing 210044,China;2.Department of Geographical Information Science,Nanjing University,Nanjing 210093,China)
 全文: PDF(681 KB)  
摘要:

随着卫星遥感和信息提取技术的快速发展,地理信息的自动更新成为可能。道路是重要的人工地物,是地理信息数据的重要组成部分,从遥感图像上提取道路信息以更新地理信息数据库成为近年来的研究热点之一。通过总结遥感图像道路信息自动提取的发展历程,归纳了常用的道路信息提取方法,并对各个方法的特点进行了分析,在此基础上分析了遥感图像道路信息提取中的不足,最后对以后道路信息提取的研究进行了展望。

关键词: 遥感图像道路提取方法综述展望    
Abstract:

With the rapid development of remote sensing and information extraction technology,it is possible to automatically update the geographic information.The road is important manmade object and is component of geographic information data.Road information exacted from remotely sensed imagery to update the GIS database has become a hot research spot for many years.This paper summarizes the course of development on road extraction from imagery,and review main methods of road extraction,template matching,knowledge method,Snakes model,dynamic programming,ridge and valley exaction method,morphological method,Hough transform,multi-scale method,method based on segmentation and other techniques for road exaction as well.The characteristics of various methods and insufficient of road extraction from remote sensing imagery were analyzed.Finally,subsequent studies were prospected.

Key words: Remote sensing image    Road    Extraction methods    Review    Prospects
收稿日期: 2008-09-26 出版日期: 2010-01-20
:  TP 751  
基金资助:

国家高技术研究发展计划(2008AA12Z106)、国家自然科学基金(40801166)、南京信息工程大学科研基金联合资助。

作者简介: 王培法(1980- )|男|讲师|主要从事高分辨率遥感图像信息提取研究。E-mail:wangpeifa1980@163.com。
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引用本文:

王培法,王丽,冯学智,肖鹏峰. 遥感图像道路信息提取方法研究进展[J]. 遥感技术与应用, 2009, 24(3): 284-290.

WANG Pei-fa,WANG Li,FENG Xue-zhi,XIAO Peng-feng. Review of Road Extraction from Remote Sensing Images. Remote Sensing Technology and Application, 2009, 24(3): 284-290.

链接本文:

http://www.rsta.ac.cn/CN/10.11873/j.issn.1004-0323.2009.3.284        http://www.rsta.ac.cn/CN/Y2009/V24/I3/284

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