Full-Text Search:
Home|Journal Papers|About CNKI|User Service|FAQ|Contact Us|中文
《Acta Geodaetica Et Cartographic Sinica》 2004-04
Add to Favorite Get Latest Update

Road Extraction from High-resolution Remotely Sensed Image Based on Morphological Segmentation

ZHU Chang-qing~(1,2), WANG Yao-ge~3, MA Qiu-he~2, SHI Wen-zhong~4(1.Institute of Geodesy and Geophysics, Chinese Academy of Science, Wuhan 430077, China; 2. Institute of Surveying and Mapping, Information Engineering University, Zhengzhou 450052, China; 3. Institute of Science, Information Engineering University, Zhengzhou 450052, China; 4. Department of Land Surveying and Geo-Informatics,The Hong Kong Polytechnic University, Hong Kong,China)  
Based on grey level mathematical morphology, this paper presents a newly developed approach to extract road network from high-resolution remotely sensed image. First, the image is segmented based on grey level morphological characteristics, and basic road network can be obtained. Then final road network is extracted from the basic road network by line match method. The proposed approach in the paper can be adapted for road extraction from the remotely sensed image where road cannot be differentiated with background clearly. And the experiments also indicate that the proposed approach is efficient for extracting road network from remotely sensed image.
【Fund】: 国家自然科学基金项目(40176032)
【CateGory Index】: P237
Download(CAJ format) Download(PDF format)
CAJViewer7.0 supports all the CNKI file formats; AdobeReader only supports the PDF format.
©2006 Tsinghua Tongfang Knowledge Network Technology Co., Ltd.(Beijing)(TTKN) All rights reserved