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REMOTE SENSING FOR LAND & RESOURCES    2016, Vol. 28 Issue (1) : 63-71     DOI: 10.6046/gtzyyg.2016.01.10
Technology and Methodology |
Auto-extraction of road intersection from high resolution remote sensing image
CAI Hongyue1,2, YAO Guoqing3
1. ChinaRS Geoinformatics Co., Ltd, Tianjin 300384, China;
2. Tianjin High Resolution Remote Sensing Information Technology Enterprise Key Lab, Tianjin 300384, China;
3. College of Information Engineering, China University of Geosciences(Beijing), Beijing 100083, China
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Abstract  

Road intersection is one of the most important parts of road network, and extraction of road intersection information plays a significant role in such aspects as road network extraction, image registration and vehicle navigation. However, the research on extracting road intersections from remote imagery is insufficient. In view of the characteristics of road intersections in high resolution remote sensing imagery, the authors propose an approach to auto-extraction of road intersection in this paper. On the basis of image preprocessing, detection of homogeneous circular area by multi-scale structure elements was firstly used to extract alternative road intersections, which included gradient transformation and morphological transformation. Secondly, feature extraction for alternative road intersections was processed in order to further refine the result and get the central position for each choice. Finally, angular texture signature was extracted for each central position and road intersections were identified by valley finding. The experimental results show that the method presented in this paper can extract urban road intersections efficiently and has fairly good accuracy for complex urban context.

Keywords fractional vegetation coverage      Radar vegetation index      dimidiate pixel model      polarimetric decomposition      Changting county     
:  TP79  
Issue Date: 27 November 2015
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HE Haiyan
LING Feilong
WANG Xiaoqin
LIANG Zhifeng
Cite this article:   
HE Haiyan,LING Feilong,WANG Xiaoqin, et al. Auto-extraction of road intersection from high resolution remote sensing image[J]. REMOTE SENSING FOR LAND & RESOURCES, 2016, 28(1): 63-71.
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https://www.gtzyyg.com/EN/10.6046/gtzyyg.2016.01.10     OR     https://www.gtzyyg.com/EN/Y2016/V28/I1/63

[1] Talal T M,El-Sayed A,Hebaishy M,et al.Extraction of roads from high-resolution satellite images with the discrete wavelet transform[J].Sensing and Imaging:An International Journal,2013,14(1/2):29-55.

[2] 王双,曹国.一种基于改进path opening的道路提取新方法[J].计算机科学,2014,41(2):285-289. Wang S,Cao G.New method for road extraction based on modified path opening algorithm[J].Computer Science,2014,41(2):285-289.

[3] Shi W Z,Miao Z L,Wang Q M,et al.Spectral-spatial classification and shape features for urban road centerline extraction[J].IEEE Geoscience and Remote Sensing Letters,2014,11(4):788-792.

[4] 周绍光,陈超,岳建平,等.形状先验和图割的高分辨率遥感影像道路段提取[J].测绘学报,2014,43(1):60-65. Zhou S G,Chen C,Yue J P.Extracting roads from high-resolution RS images based on shape priors and graph cuts[J].Acta Geodaetica et Cartographica Sinica,2014,43(1):60-65.

[5] 林祥国,张继贤,刘正军,等.用改进的剖面匹配算子提取高分辨率遥感影像上带状道路[J].测绘科学,2009,34(4):64-66,126. Lin X G,Zhang J X,Liu Z J,et al.Semi-automatic extraction of ribbon road form high resolution remotely sensed imagery by improved profile matching algorithm[J].Science of Surveying and Mapping,2009,34(4):64-66,126.

[6] Niu X T.A semi-automatic framework for highway extraction and vehicle detection based on a geometric deformable model[J].ISPRS Journal of Photogrammetry and Remote Sensing,2006,61(3/4):170-186.

[7] Trinder J C,Wang Y D.Knowledge-based road interpretation in aerial images[J].International Archives of Photogrammetry and Remote Sensing,1998,32(4):635-640.

[8] Gamba P,Dell'Acqua F,Lisini G.Improving urban road extraction in high-resolution images exploiting directional filtering,perceptual grouping,and simple topological concepts[J].IEEE Geoscience and Remote Sensing Letters,2006,3(3):387-391.

[9] 顾丹丹,汪西莉.结合区域生长和水平集的遥感影像道路提取[J].计算机应用,2010,30(2):433-436,440. Gu D D,Wang X L.Road extraction from remote sensing images combining region growing with level set[J].Journal of Computer Applications,2010,30(2):433-436,440.

[10] 李伟.遥感图像中的道路提取[J].自动化博览,2006,23(5):20-23. Li W.Road extraction from remote sensing images[J].Automation Panorama,2006,23(5):20-23.

[11] 吴亮,胡云安.参考道路交叉点的飞行器视觉辅助导航[J].北京航空航天大学学报,2010,36(8):892-895. Wu L,Hu Y A.Scheme for vision-aided navigation in flight with reference of road intersections[J].Journal of Beijing University of Aeronautics and Astronautics,2010,36(8):892-895.

[12] Laptev I,Lindeberg T,Eckstein W,et al.Automatic extraction of roads from aerial images based on scale space and snakes[J].Machine Vision and Applications,2000,12(1):23-31.

[13] Chiang Y Y,Knoblock C A,Shahabi C,et al.Automatic and accurate extraction of road intersections from raster maps[J].GeoInformatica,2009,13(2):121-157.

[14] Mokhtarian F,Suomela R.Robust image corner detection through curvature scale space[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,1998,20(12):1376-1381.

[15] Koutaki G,Uchimura K.Automatic road extraction based on cross detection in suburb[C]//Bouman C A,Miller E L.Computational Imaging II.San Jose,CA:SPIE,2004:337-344.

[16] Barsi A,Heipke C.Detecting road junctions by artificial neural networks[C]//Proceedings of the 2nd GRSS/ISPRS Joint Workshop on Remote Sensing and Data Fusion over Urban Areas.Berlin,Germany:IEEE,2003:129-132.

[17] 陈晓飞,薛峰,王润生.航空照片中道路交叉口的自动检测[J].模式识别与人工智能,2000,13(1):83-86. Chen X F,Xue F,Wang R S.Intersections automatic detection in aerial photos[J].Pattern Recognition and Artificial Intelligence,2000,13(1):83-86.

[18] Haverkamp D.Extracting straight road structure in urban environments using IKONOS satellite imagery[J].Optical Engineering,2002,41(9):2107-2110.

[19] 周绍光,刘娟娟,陈仁喜.从高分辨率遥感影像中提取城市道路的新方法[J].计算机工程与应用,2010,46(32):216-219. Zhou S G,Liu J J,Chen R X.New method to extract roads in urban area from high-resolution remote sensing imagery[J].Computer Engineering and Applications,2010,46(32):216-219.

[20] Wan Y C,Shen S H,Song Y,et al.A road extraction approach based on fuzzy logic for high-resolution multispectral data[C]//Proceedings of the 4th International Conference on Fuzzy Systems and Knowledge Discovery.Haikou:IEEE,2007:203-207.

[21] 张睿,张继贤,李海涛.基于角度纹理特征及剖面匹配的高分辨率遥感影像带状道路半自动提取[J].遥感学报,2008,12(2):224-232. Zhang R,Zhang J X,Li H T.Semi-automatic extraction of ribbon roads from high resolution remotely sensed imagery based on angular texture signature and profile match[J].Journal of Remote Sensing,2008,12(2):224-232.

[22] Hu J X,Razdan A,Femiani J C,et al.Road network extraction and intersection detection from aerial images by tracking road footprints[J].IEEE Transactions on Geoscience and Remote Sensing,2007,45(12):4144-4157.

[23] 陈卓,马洪超,李云帆.结合角度纹理信息和Snake方法从LiDAR点云数据中提取道路交叉口[J].国土资源遥感,2013,25(4):79-84.doi:10.6046/gtzyyg.2013.04.13. Chen Z,Ma H C,Li Y F.Extraction of road intersection from LiDAR point cloud data based on ATS and Snake[J].Remote Sensing for Land and Resources,2013,25(4):79-84.doi:10.6046/gtzyyg.2013.04.13.

[24] 程江华,高贵,库锡树,等.高分辨率SAR图像道路交叉口检测与识别新方法[J].雷达学报,2012,1(1):91-95. Cheng J H,Gao G,Ku X S,et al.A novel method for detecting and identifying road junctions from high resolution SAR images[J].Journal of Radars,2012,1(1):91-95.

[25] 冯伍,张俊兰,苗秋瑾.几种典型边缘检测算子的评估[J].电子设计工程,2011,19(4):131-133. Feng W,Zhang J L,Miao Q J.Evaluation of several typical edge detection operator[J].Electronic Design Engineering,2011,19(4):131-133.

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