计算机与现代化Issue(11)：55-61,7.DOI:10.3969/j.issn.1006-2475.2017.11.011
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
刘欢 1阎镇2
作者信息
- 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
- 折叠
摘要
Abstract
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Key words
high resolution remote sensing images/road extraction/improved K-means algorithm/feature fusion/mathematical morphology分类
信息技术与安全科学引用本文复制引用
刘欢,阎镇..基于改进的K-means法的高分辨率遥感影像道路提取[J].计算机与现代化,2017,(11):55-61,7.
