摘要
从高分辨率遥感影像中提取道路信息具有重要的现实意义。针对现有影像分类方法无法直接获取高精度道路网信息及自动化程度低的问题,本文提出了一种基于OSM(OpenStreetMap)矢量路网辅助的道路提取方法,实现了对高分辨率遥感影像道路快速精确的自动提取。首先,采用灰度形态学的腐蚀、膨胀及开闭操作对遥感影像进行预处理;然后通过OSM路网提供的先验信息,对模糊C均值算法进行改进,并将输入的遥感影像粗分为3类;接着以粗分类结果作为分类特征,通过OSM矢量路网自动获取道路样本,使用支持向量机进行精分类,并采用粒子群优化算法选取最优分类参数;最后对分类结果进行形态学后处理,得到精确的道路网信息。利用两组Google Earth影像进行试验,结果表明,本文算法在道路网提取精度上要优于对比算法。
It is of great practical significance to extract road information from high-resolution remote sensing images.In view of the fact that the existing image classification methods can not directly obtain the high-precision road network information and the degree of automation is low , this paper presents a road extraction method based on the OSM (OpenStreetMap) vector road network guidance to achieve fast and accurate automatic road extraction of high resolution remote sensing images. Firstly, remote sensing images are preprocessed by the gray morphological corrosion, expansion and opening and closing operations.Through the prior information provided by the OSM network, the fuzzy C-means algorithm is improved and the input remote sensing images are roughly divided into three categories.Then the rough classification results are taken as the classification features, and the road samples are automatically selected by the OSM vector network.Using support vector machines for fine classification,and the optimal classification parameters are selected by means of the particle swarm optimization. Finally, we post-process the classification results to get a complete road network. Experiments using two groups of Google Earth images show that the proposed algorithm outperforms the comparison algorithm in the accuracy of road network extraction.
作者
程效猛
郑浩
眭海刚
冯文卿
CHENG Xiaomeng;ZHENG Hao;SUI Haigang;FENG Wenqing(l State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing,Wuhan University,Wuhan 430079,China 2.The General Armament Development Department Project Management Center,Beijing 100034,China)
出处
《测绘通报》
CSCD
北大核心
2018年第9期19-23,共5页
Bulletin of Surveying and Mapping
基金
国家自然科学基金(41771457)
国家重点研发计划(2016YFB0502603)
关键词
道路提取
矢量引导
模糊C均值
支持向量机
粒子群优化
road extraction
vector guidance
fuzzy C-means
support vector machines
particle swarm optimization