遥感影像道路的多点同时快速行进提取方法
Road Extraction Method Using Multi-points Fast Marching and Minimum Paths
查看参考文献12篇
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文摘
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研究提出了一种基于多点同时快速行进构建最短路径,提取遥感影像道路的方法。该方法依据道路灰度、梯度或边缘特征构建行进速度项,以多个道路特征点作为起始种子点,多点同时快速行进提取遥感影像最小能量图,并以起始种子点为中心点,按照最小能量值对图像区域进行划分,提取相邻区域对应起始点对行进过程中最先接触的鞍点,设定判定准则从鞍点中选取有效鞍点,剔除可能提取的错误捷径,从有效鞍点出发,沿最小能量值减小且梯度变化最快方向逆向搜索至对应起始点对提取最短路径,最终连接最短路径作为提取的道路。研究将该方法应用到ETM+、IKONOS、航空影像等遥感影像数据中,进行不同空间分辨率、不同大小、不同路网条件下道路提取的实验。结果表明该方法仅需少量的道路特征点作为先验知识,即可实现各类型道路信息的提取。提取的道路连续,无需细化、断线连接等后处理,能够实现多条道路的同时提取,具有较高的提取效率。 |
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其他语种文摘
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This paper introduced fast marching and minimum path into road extraction from remotely sensed images and proposed a new road extraction method.The work builds on a novel variant of fast marching approach,named as multi-points fast marching.The underlying idea is to calculate minimum action map with multi-points propagating simultaneously.Efficacious saddle points are selected with judgment criterion to exclude potential erroneous shortcuts.The extraction roads are continuous line features between couples of starting points that dispense with thinning and broken lines connection.The programming implementation of the method is given and remote sensing imageries of ETM+,IKONOS and airborne images have been taken as case studies.The test images have different spatial resolution,size and road network conditions.The experiment shows that multi-points fast marching could extract roads from 161×163 ETM+ image in 0.10 s,1 653×1 630 IKONOS image in 21.20s,1 579×1 698 airborne image in 20.80 s.The results demonstrated that the proposed method can extract multiple roads with high efficiency and little post-processing. |
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来源
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遥感技术与应用
,2011,26(3):294-302 【扩展库】
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关键词
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遥感影像
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道路提取
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快速行进
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最小能量图
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最短路径
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地址
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南京大学地理与海洋科学学院地理信息科学系, 江苏, 南京, 210093
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语种
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中文 |
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文献类型
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研究性论文 |
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ISSN
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1004-0323 |
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学科
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自动化技术、计算机技术 |
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基金
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国家自然科学基金项目
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文献收藏号
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CSCD:4240199
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参考文献 共
12
共1页
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1.
史文中. 从遥感影像提取道路特征的方法综述与展望.
测绘学报,2001,30(3):257-262
|
CSCD被引
84
次
|
|
|
|
|
2.
武冰. 一种引入角点特征的遥感图像道路提取方法.
计算机仿真,2006,23(10):209-213
|
CSCD被引
1
次
|
|
|
|
|
3.
马力. 上下文信息在道路提取中的分类与应用.
地理信息世界,2008,8(4):58-60
|
CSCD被引
2
次
|
|
|
|
|
4.
Cohen L D. Global Minimum for Active Contour Models:a Minimum Path Approach.
International Journal of Computer Vision,1997,24(1):57-78
|
CSCD被引
11
次
|
|
|
|
|
5.
Cohen L D. Multiple Contour Finding and Perceptual Grouping Using Minimum Paths.
Journal of Mathematical Imaging and Vision,2001,14(3):225-236
|
CSCD被引
1
次
|
|
|
|
|
6.
Cohen L D. Grouping Connected Components Using Minimum Path Techniques Application to Reconstruction of Vessels in 2D and 3D Images.
IEEE Computer Society Conference on Computer Vision and Pattern Recognition,CVPR01 2001(Paris 9-Dauphine),2001
|
CSCD被引
1
次
|
|
|
|
|
7.
Cohen L D.
Handbook of Mathematical Models in Computer Vision,2006:97-111
|
CSCD被引
1
次
|
|
|
|
|
8.
Deschamps T. Fast Extraction of Minimum Paths in 3D Images and Applications to Virtual Endoscopy.
Medical Image Analysis,2001,5(4):281-299
|
CSCD被引
14
次
|
|
|
|
|
9.
姜慧研. 基于改进的双快速行进法的图像分割方法.
系统仿真学报,2008,20(3):803-810
|
CSCD被引
11
次
|
|
|
|
|
10.
Fethallah B. Fast Object Segmentation by Growing Minimum Paths from a Single Point on 2D or 3D Images.
Journal of Mathematical Imaging and Vision,2009,33(2):201-221
|
CSCD被引
1
次
|
|
|
|
|
11.
Sethian J A. Evolution,Implementation,and Application of Level Set and Fast Marching Methods for Advancing Fronts.
Journal of Computational Physics,2001,169(2):503-555
|
CSCD被引
34
次
|
|
|
|
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12.
Liron Y. O(N)Implementation of the Fast Marching Algorithm.
Journal of Computational Physics,2006,212(2):393-399
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CSCD被引
1
次
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|
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