融合纹理和形状特征的高分辨率遥感影像道路提取  

Road Extraction from High-resolution Remote Sensing Images Based on Texture and Shape Features

作　　者：王昆[1] 万幼川[1] 屈颖[1] 

机构地区：[1]武汉大学遥感信息工程学院,武汉430079

出　　处：《遥感信息》2010年第5期7-11,共5页Remote Sensing Information

基　　金：国家863计划(2006AA12Z136);国家支撑计划:村镇地理信息采集技术与设备研发

摘　　要：提出一种结合纹理和形状特征提取道路信息的方法。首先利用灰度共生矩阵提取纹理特征,并将其应用于最大似然分类中提取面状道路,然后利用形态学方法分割道路与其相连地物,最后利用提出的3个形状指数(凹度、精密度、偏心角)有效地识别和区分了道路与非道路地物,并最终实现了提纯道路的目的。实验结果证明,该方法可以准确地提取主干道路网,剔除非道路地物的影响。As one of the most important features in geographic database,road extraction is always the research focus in the field of remote sensing.This paper proposes a new method integrating texture and shape features for road extraction.Firstly,the texture feature obtained by gray-level co-occurrence matrix（GLCM） is applied to maximum likelihood classification and to extract the road surface image;then the morphological methods are utilized to segment the road and non-road objects;finally,three shape features are presented to refine the road information and eliminate the influence of non-road objects,such as buildings and parking lots.Experimental results indicate that this method is efficient to extract the central road network accurately.

关 键 词：高分辨率遥感影像 道路提取 纹理 灰度共生矩阵 形态学 形状特征 凹度 精密度 偏心角 

分 类 号：TP79[自动化与计算机技术—检测技术与自动化装置]