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REMOTE SENSING FOR LAND & RESOURCES    2012, Vol. 24 Issue (1) : 13-16     DOI: 10.6046/gtzyyg.2012.01.03
Technology and Methodology |
A New Approach to Automatic Positioning of Road Junctions in High Spatial Resolution Remotely Sensed Imagery
ZHANG Wei-wei1,2, MAO Zheng-yuan1,2
1. Key Laboratory of Spatial Data Mining and Information Sharing of Ministry of Education, Fuzhou University, Fuzhou 350002, China;
2. Provincial Spatial Information Engineering Research Center, Fuzhou University, Fuzhou 350002, China
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Abstract  On the basis of systematically inducing and analyzing the methods to extract road junctions from remotely sensed imagery,a new approach to automatically positioning road junctions in high spatial resolution images is presented in this paper. The related algorithm includes the following steps: firstly,the homogeneous areas are obtained by lower gradient operator; then,waters,shadows and small areal distracting features are removed one by one; after that,the straight lines are detected in the binary image by means of Hough transform; finally,the detected straight lines are sorted according to the frequency with which they appear,and the road junctions are indicated with the average coordinates of the intersections of several top frequent straight lines each of which at least has one intersection angle larger than the predetermined threshold. In the case study,an intersection and a junction of three roads were located in local urban area of Fuzhou by using QuickBird panchromatic image as sample data,showing that the proposed approach,with robustness against spectral confusion and confused features,can efficiently and accurately locate road junctions.
Keywords Remote sensing reflectance      Scattering coefficient      Absorption coefficient      Optical field distribution      Solar zenith     
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TP 751.1

 
Issue Date: 07 March 2012
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QIAN Hao-zhong
ZHAO Qiao-hua
HE Jin-hai
SUN De-yong
JIANG Yu-wei
TAO Rong-yin
Cite this article:   
QIAN Hao-zhong,ZHAO Qiao-hua,HE Jin-hai, et al. A New Approach to Automatic Positioning of Road Junctions in High Spatial Resolution Remotely Sensed Imagery[J]. REMOTE SENSING FOR LAND & RESOURCES, 2012, 24(1): 13-16.
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https://www.gtzyyg.com/EN/10.6046/gtzyyg.2012.01.03     OR     https://www.gtzyyg.com/EN/Y2012/V24/I1/13
[1] Baumgartner A,Steger C,Mayer H,et al.Automatic Road Extraction in Rural Areas[J].International Archives of Photogrammetry and Remote Sensing,1999,32(3;SECT 2W5):107-112.
[2] Mayer H,Laptev I,Baumgartner A.Multi-scale and Snakes for Automatic Road Extraction[J].Computer Vision—ECCV’98,1998:720-733.
[3] Hinz S,Baumgartner A,Steger C,et al.Road Extraction in Rural and Urban Areas[J].Semantic Modeling for the Acquisition of Topographic Information from Images and Maps,1999:7-27.
[4] Barsi A,Heipke C,Willrich F.Junction Extraction by Artificial Neural Network System-JEANS[J].International Archives of Photogrammetry Remote Sensing and Spatial Information Sciences,2002,34(3/B):18-21.
[5] Teoh C Y,Sowmya A.Junction Extraction from High Resolution Images by Composite Learning[J].International Archives of Photogrammetry and Remote Sensing,2000,33(B3/2;PART 3):882-888.
[6] Boichis N,Viglino J M,Cocquerez J.Knowledge Based System for the Automatic Extraction of Road Intersections from Aerial Iimages[J].International Archives of Photogrammetry and Remote Sensing,2000,33(B3):27-34.
[7] Chen C C,Thakkar S,Knoblock C,et al.Automatically Annotating and Integrating Spatial Datasets[J].Advances in Spatial and Temporal Databases,2003:469-488.
[8] Ravanbakhsh M,Heipke C,Pakzad K.Knowledge-based Road Junction Extraction from High-resolution Aerial Images[J].IEEE,2007.
[9] Wiedemann C.Improvement of Road Crossing Extraction and External Evaluation of the Extraction Results[J].International Archives of Photogrammetry Remote Sensing and Spatial Information Sciences,2002,34(3/B):297-300.
[10] 史文中,朱长青,王昱.从遥感影像提取道路特征的方法综述与展望[J].测绘学报,2001,30(3):257-262.
[11] 陈震,高满屯,杨声云.基于Hough变换的直线跟踪方法[J].计算机应用,2003,23(10):30-32.
[12] Hough P V C.Method and Means for Recognizing Complex Patterns[P].US:Patent 3 069 654,1962.
[13] Duda R O,Hart P E.Use of the Hough Transformation to Detect Lines and Curves in Pictures[J].Communications of the ACM,1972,15(1):11-15.
[14] Sonka M,Hlavac V,Boyle R,et al.图像处理:分析与机器视觉[M].艾海舟,武勃,等译.北京:人民邮电出版社,2003.
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