A NEW METHOD OF ROAD EXTRACTION FROM HIGHRESOLUTION REMOTE SENSING IMAGE

摘要

It is still an open problem to extract objects feature from high-resolution remote sensing image, although this topic had been intensively investigated and many methods had been put forwards. All works for this thesis are focused on modern urban road and include the following four steps: image pre-processing, threshold calculation, feature extraction for straight line and curved line, target reconstruction. In this contribution, a new and semi-automatic approach is proposed based on phase classification. Firstly, basic road network can be obtained from high-resolution remote sensing image based on grey level mathematical morphology and canny algorithm and then road information can be exactly extracted by means of the “grey” parameters which are various for different kinds of road models based on the theory of phase-based classification. Additionally, the proposed method can also be employed to elevate urban highways, especially for the curve parts of which. The extracting results are reasonable.