节点文献

基于地物光谱特征分析的高分辨率遥感图像水上桥梁提取

Extraction of Bridge over Water from High-Resolution Remote Sensing Images Based on Spectral Characteristics of Ground Objects

  • 推荐 CAJ下载
  • PDF下载
  • 不支持迅雷等下载工具,请取消加速工具后下载。

【作者】 陈超秦其明陈理王金梁刘明超温奇

【Author】 CHEN Chao1,QIN Qi-ming1,CHEN Li1,WANG Jin-liang1,LIU Ming-chao1,WEN Qi2 1.Institute of Remote Sensing and Geographic Information System,Peking University,Beijing 100871,China 2.National Disaster Reduction Center of China(NDRCC),Ministry of Civil Affairs,Beijing 100124,China

【机构】 北京大学遥感与地理信息系统研究所民政部国家减灾中心

【摘要】 水上桥梁是一种典型的人造目标。利用高分辨率遥感图像进行水上桥梁提取,对于民用、军用和商业都具有重要意义。论文在分析地物光谱特征的基础上,提出了一种利用高分辨率近红外波段遥感图像进行水上桥梁提取的方法。首先,根据水体在近红外波段的光谱特征,采用迭代法选取阈值提取水体信息,以限制桥梁提取的空间范围;然后,对水体信息进行数学形态学运算,以连接因桥梁而断开的水体;其次,对数学形态学操作前后的水体信息进行叠加分析,以提取候选桥梁目标;最后,在桥梁先验特征知识的辅助下,去除伪桥梁目标。论文设计了仿真实验,以验证方法的有效性和适用性。实验结果表明,基于地物光谱特征分析的高分辨率遥感图像水上桥梁提取方法是行之有效的。

【Abstract】 Bridge over water is a typical man-made target.Using the high-resolution optical remote sensing images,to extract bridge over water appears significant for civilian,military,and commerce.First,in the present paper,according to the spectral characteristics of water in near-infrared spectrum,water information is extracted using the iterative method for the threshold value,to limit the spatial extent of bridge extraction.Second,mathematical morphology is performed on the water information,to connect the separated water bodies due to the presence of bridges on the image.Third,overlay analysis is conducted between the two images before and after mathematical morphology operations,to extract the potential bridge.Finally,based on priori-knowledge of the bridge,the false bridge is removed.In this paper an experimental area is selected to verify the effectiveness and applicability of the method.Experimental results show that the method is effective for bridge extraction over water by using high-resolution remote sensing images based on spectral characteristics of ground objects.

【基金】 国家科技重大专项项目;国家高技术研究发展计划(863计划)主题项目(2012AA121305,2011BAB01B06)资助
  • 【文献出处】 光谱学与光谱分析 ,Spectroscopy and Spectral Analysis , 编辑部邮箱 ,2013年03期
  • 【分类号】TP751
  • 【被引频次】13
  • 【下载频次】610
节点文献中: 

本文链接的文献网络图示:

本文的引文网络