从高分辨率遥感影像中提取城市道路的新方法

在综合几种现有算法优点的基础上，提出一种新的道路提取策略。首先以角度纹理特性法分割原始影像；接着利用直线匹配原理剔除初始分割结果中的非道路地物，得到更为规则的道路条带；然后通过形态学手段获得道路中心线，并将每条中心线拆分为多段直线；结合上下文知识的马尔可夫模型被用于组织道路段的中心线，从而恢复完整道路网。实验结果表明：新方法具有良好的性能，可以从高分辨IKONOS遥感影像中提取出复杂的城市道路。

New method to extract roads in urban area from high-resolution remote sensing imagery

A new scheme to extract roads in urban area is presented by taking the advantages of several existing methods.The original IKONOS image is segmented using the angular texture signature principle.Then the line segment matching approach is utilized to remove non-road targets from the segmented result,so that roads boundaries appear more regular.In the third step central lines of all roads are obtained with the aid of some morphological algorithms,furthermore a curve central line is broken into piecewise lines.Finally central road line segments are grouped to restore the whole road network using Markovian model and context knowledge.Experimental results show that the proposed method is efficient for extracting roads in urban area from high-resolution images.