Remote sensing image road network automatic extraction method with navigation data assistance

Abstract

The invention provides a remote sensing image road network automatic extraction method with navigation data assistance. The method comprises the steps that registration of navigation data and a remote sensing image is performed; vector data is utilized to extract road sections; intersection pixel structure indexes are utilized to extract road intersections; a road network is extracted based on adaptive cluster learning; the extracted road sections and road intersections are connected to form the road network, and a newly-added road object in the remote sensing image is detected according to known road characteristics; and last, the road is verified. According to the method, the remote sensing image and the navigation road network data are adopted as input data sources, location, geometrical, topological and semantic information in the navigation road network data and scene characteristics in the high-resolution remote sensing image are comprehensively utilized, and the task of automatic road network element data extraction is completed in combination with realistic road structure priori knowledge, etc. The method has high practicability and high accuracy.

Description

technical field [0001] The invention relates to the technical field of remote sensing image applications, in particular to a method for automatically extracting road networks from remote sensing images aided by navigation data. Background technique [0002] With the advancement of my country's urbanization process and the rapid development of economic construction, the rapid update of road network data has become more and more important for the public and industry applications. The rapid acquisition and update of road element data has become the basis of my country's basic geographic information construction. important task. At present, the comprehensive internal adjustment based on high-resolution remote sensing images is the main method for updating basic geographic elements including road networks. There are great advantages to doing basic geographic information updates. Compared with the update of actual ground measurement data in the field, the office judgment and mapp...

AI Technical Summary

Problems solved by technology

On the other hand, roads are represented as a collection of various ground objects, such as vehicles, road signs, street lines, street trees, etc., which makes the internal characteristics of road elements have great heterogeneity. Large feature correlation, which makes it difficult for automatic road extraction methods to accurately identify road objects; in addition, due to shadows and other occlusions, automated road extraction tasks become more difficult

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