摘要
本文研究了基于道路轨迹预测模型的遥感影像分类方法,回顾遥感图像道路提取的研究背景,分析了影响道路提取的关键因素,包括图像分辨率和算法的自动化程度。文章详细阐述了道路要素的遥感影像提取方法,包括快速道路、主干道和次干道的提取策略。在快速道路提取方面,采用面向对象分类思想和规则集构建技术;在主干道提取中,则利用循环规则集构建和数学形态学处理相结合的方法;对于次干道提取,文章提出了图像预处理和次干道线特征提取的步骤。这些方法为遥感影像中的道路分类和提取提供了有效的技术支撑。
In this paper,remote sensing image classification method has been studied based on road trajectory prediction model,research background of remote sensing image road extraction has been reviewed,and key factors affecting road extraction have been analyzed,including image resolution and algorithm automation degree.Remote sensing image extraction methods of road elements,including the extraction strategies of fast road,main road and secondary road.In the aspect of fast path extraction,object-oriented classification and rule set construction technology are adopted.In main road extraction,the method combining the construction of cyclic rule set and mathematical morphology processing has been used.For sub-trunk extraction,the steps of image preprocessing and sub-trunk feature extraction have been proposed.These methods will provide effective technical support for road classification and extraction in remote sensing images.
作者
张名华
张洪军
石建
赵春丽
郑伟安
李天鹤
ZHANG Minghua;ZHANG Hongjun;SHI Jian;ZHAO Chunli;ZHENG Weian;LI Tianhe(Longkou Bureau of Natural Resources and Planning,Shandong Yantai 265700,China;Shandong Provincial Institute of Land Surveying and Mapping,Shandong Ji'nan 250102,China)
出处
《山东国土资源》
2024年第8期37-41,共5页
Shandong Land and Resources
基金
山东省自然资源厅2024年省级基础测绘项目(鲁自然资字〔2024〕32号)。
关键词
高分辨率遥感影像
道路提取
道路轨迹预测模型
High-resolution remote sensing image
road extraction
road trajectory prediction model
