Road extraction from high resolution remote sensing image based on mathematics morphology

Hongbin Ma; Yahong Zhao; Yongsheng Chen

doi:10.1117/12.813225

7 November 2008 Road extraction from high resolution remote sensing image based on mathematics morphology

Hongbin Ma, Yahong Zhao, Yongsheng Chen

Proceedings Volume 7147, Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Classification of Remote Sensing Images; 71470O (2008) https://doi.org/10.1117/12.813225
Event: Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Geo-Simulation and Virtual GIS Environments, 2008, Guangzhou, China

Abstract

Extracting target information from the remote sensing images has been becoming an important method of updating the spatial geography data. With the development of spatial technology, sensor technology, digital image processing technology and the computer pattern recognition technology, how to extract target information from the high resolution remote sensing images has become the target of many researchers. Based on the feasibility experimental study of road extraction using Mathematics Morphology, this paper put forward one kind of road extraction method with Mathematics Morphology as primarily path and seed growing as auxiliary path. City road network information in high resolution remote sensing image is taken as the research object. In this paper Mathematics Morphology method and the segment method of Support Vector Machine are used. This paper presents that the combination of Mathematics Morphology and seed growing method has priority to Mathematics Morphology or seed growing used respectively, especially has the superiority in extracting the road detail information.

Citation Download Citation

Hongbin Ma, Yahong Zhao, and Yongsheng Chen "Road extraction from high resolution remote sensing image based on mathematics morphology", Proc. SPIE 7147, Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Classification of Remote Sensing Images, 71470O (7 November 2008); https://doi.org/10.1117/12.813225

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