利用模板匹配和BSnake算法准自动提取遥感影像面状道路

针对已有的遥感影像面状道路提取策略在自动化程度、效率及精度方面的不足,提出了一种新的快速有效的准自动提取方法。遥感影像上各种面状道路的提取实验证明了算法的有效性,在自动化程度、速度和精度上均有明显成效。

Quasi-automatic Extraction of Zonal Roads from Remote Sensing Images Using Template Matching and BSnake Model

In this paper,a new method of quasi-automatic extraction of zonal roads is put forward.Based on research on roads’ feature in high resolution RS images,this paper uses two seed points chosen on road surface to automatically search original information of roads;Then,we can establish standard road template,and match it with new road templates got by moving and rotating standard template to compute new direction,center point and edge points of next road segment;Through constantly updating road standard template,direction and center point,automatically obtain a series of edge points distributing on the two-edge of road;Use Snake Model to dynamically adjust edge points and accurately position them on the true edge;Lastly,solve B-spline curve of control points to denote the two borders.The results show the research is effective and viable;Meanwhile,the research makes great advance in the degree of automation,efficiency and accuracy.