Multi-scale Road Extraction Using Local and Global Grouping Criteria

In this paper we combine two approaches for road extraction. The first approach makes use of multiple scales to detect roads segments and employs local grouping criteria and also context information to extract the road network. This approach is suitable for aerial imagery with a resolution of 0.2–0.5 m. The second approach was designed to extract roads from satellite imagery and can be applied to resolutions of 2–5 m. It fuses lines extracted from different channels for road extraction and exploits especially the connectivity properties of roads, i.e., global network criteria for road extraction. By combining the two approaches we can reduce the effort for selecting appropriate parameters, because both help each other to get rid of some individual deficiencies. In addition, the evaluation of the extracted road network showed significant improvements compared to the results we get by applying each approach on its own.