基于改进的K-means法的高分辨率遥感影像道路提取  

Road Extraction in High Resolution Remote Sensing Images Based on Improved K-means Algorithm

作　　者：刘欢[1,2] 阎镇 

机构地区：[1]中国科学院空间应用工程与技术中心太空应用重点实验室,北京100094 [2]中国科学院大学,北京100049

出　　处：《计算机与现代化》2017年第11期55-61,共7页Computer and Modernization

摘　　要：针对高分辨率遥感影像中道路提取存在的特征利用问题,提出一种基于改进的K-means算法的道路提取方法。首先根据遥感影像的具体场景进行相应的预处理;在此基础上,利用改进的K-means算法融合道路的光谱特征和纹理特征对图像进行分类,得到初始道路区域;然后利用道路的几何特征滤除非道路区域;最后采用数学形态学方法完善道路信息,得到最终结果。实验结果表明,该方法能实现复杂场景中道路提取,并拥有较好的效果。Aiming at the problem of feature extraction in road extraction in high resolution remote sensing images,a road extraction method based on improved K-means algorithm was proposed.Firstly,pretreatment was executed according to the specific scene of the target image.Secondly,improved K-means algorithm was introduced to implement spectral-textural classification to segment the image into two categories：road and nonroad groups.Thirdly,the geometric features of road were used to extract reliable road segments.Finally,mathematical morphology was used to complete the road information and get the final result.The experimental results show that our method can realize the road extraction in complex scene and has satisfactory effect.

关 键 词：高分辨率遥感影像 道路提取 改进的K均值算法 特征融合 数学形态学 

分 类 号：TP751[自动化与计算机技术—检测技术与自动化装置]