|本期目录/Table of Contents|

[1]施益强,朱晓铃,蔺方.基于多因子对象的高空间分辨率遥感影像道路提取[J].集美大学学报(自然科学版),2010,15(4):312-316.
　SHI Yi-qiang,ZHU Xiao-ling,LIN Fang.Road Extraction in High Spatial Resolution Remote Sensing ImageBased on Multi-Factor Objects[J].Journal of Jimei University,2010,15(4):312-316.
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《集美大学学报（自然科学版）》[ISSN:1007-7405/CN:35-1186/N]

卷:
第15卷
期数:
2010年第4期
页码:
312-316
栏目:
数理科学与信息工程
出版日期:
2010-07-25

文章信息/Info

Title:
Road Extraction in High Spatial Resolution Remote Sensing ImageBased on Multi-Factor Objects
作者:
施益强1; 2; 朱晓铃3; 蔺方2
(1.集美大学影像信息工程技术研究中心,福建 厦门 361021;2.集美大学理学院,福建 厦门 361021;3.厦门理工学院空间信息技术研究所,福建 厦门 361024)
Author(s):
SHI Yi-qiang1; 2; ZHU Xiao-ling3; LIN Fang2
(1.Research Center of Image Information Engineering and Technology,Jimei University,Xiamen 361021,China;2.School of Science,Jimei University,Xiamen 361021,China;3.Institute of Spatial Information Technology,Xiamen University of Technology,Xiamen 361024,China)
关键词:
高空间分辨率; 遥感影像; 多因子对象; 道路提取
Keywords:
high spatial resolution; remote sensing image; multi-factor objects; road extraction
分类号:
-
DOI:
-
文献标志码:
-
摘要:
］利用面向对象思想，综合应用光谱值、光滑度、紧凑度及长宽比等因子，分割道路对象，构建规则知识库，探讨一种基于多因子对象的高空间分辨率遥感影像道路提取方法，并以厦门市局部区域的QuickBird影像为例进行实证.结果表明：影像分割尺度为75时，道路对象被较完整分割；与传统基于单个像元光谱信息的监督分类法相比，该方法的提取精度较高
Abstract:
Using object-oriented idea,considering such factors as spectrum value,smooth, compaction and aspect ratio,segmenting the road object,building a library of rule learning,this paper proposed a method of road extraction in high spatial resolution remote sensing image based on multi-factor objects.Partial QuickBird image of Xiamen City was choosen as experimental data to verify the proposed method.The experiment result showed that the road objects were fully segmented when the segmentation scale was 75,and that the extraction precision by this method was higher than that by the traditional supervised classification based on spectrum information of single pixel

参考文献/References:

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备注/Memo

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更新日期/Last Update: 2014-06-28