Registration of satellite images based on road network map

J. Zaletelj, U. Burnik, J. Tasic
{"title":"Registration of satellite images based on road network map","authors":"J. Zaletelj, U. Burnik, J. Tasic","doi":"10.1109/ISPA.2013.6703713","DOIUrl":null,"url":null,"abstract":"This paper presents a novel approach to fully automatic satellite image registration to a local earth coordinate system based on the digital map of the road network. Automatic satellite image co-registration methods typically establish correspondences between points on the target and registered image using local image features such as SIFT, however they are not effective for multi-temporal and multi-sensor registration. As the road network is a prominent feature on the satellite images and is visible in most circumstances, we propose to map it directly to the digital road network topographic map, which is readily available in GIS databases. Our approach starts by detection of road segments in a satellite image, producing a road mask image. Small road mask patches are matched against rasterized road network map to find a set of probable patch locations. Following optimization of translation parameters, each satellite image tile is coarsely located on a road map. In a second fine optimization step, smaller road patches locations are further optimized. The algorithm produces a set of tie points, which include coordinates of satellite image pixels within local metric coordinate system. Experiments were performed on a set of 5 RapidEye images of Slovenia from different periods of the year. The results show that the average error of the points is below 1 pixel for all images, and that the reliability in terms of outlier pixels is very high.","PeriodicalId":425029,"journal":{"name":"2013 8th International Symposium on Image and Signal Processing and Analysis (ISPA)","volume":"127 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 8th International Symposium on Image and Signal Processing and Analysis (ISPA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISPA.2013.6703713","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10

Abstract

This paper presents a novel approach to fully automatic satellite image registration to a local earth coordinate system based on the digital map of the road network. Automatic satellite image co-registration methods typically establish correspondences between points on the target and registered image using local image features such as SIFT, however they are not effective for multi-temporal and multi-sensor registration. As the road network is a prominent feature on the satellite images and is visible in most circumstances, we propose to map it directly to the digital road network topographic map, which is readily available in GIS databases. Our approach starts by detection of road segments in a satellite image, producing a road mask image. Small road mask patches are matched against rasterized road network map to find a set of probable patch locations. Following optimization of translation parameters, each satellite image tile is coarsely located on a road map. In a second fine optimization step, smaller road patches locations are further optimized. The algorithm produces a set of tie points, which include coordinates of satellite image pixels within local metric coordinate system. Experiments were performed on a set of 5 RapidEye images of Slovenia from different periods of the year. The results show that the average error of the points is below 1 pixel for all images, and that the reliability in terms of outlier pixels is very high.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于路网地图的卫星图像配准
提出了一种基于路网数字地图的卫星图像局部地球坐标系自动配准的新方法。卫星图像自动配准方法通常利用SIFT等局部图像特征建立目标点与配准图像之间的对应关系,但对于多时段、多传感器的配准效果较差。由于道路网络是卫星图像上的一个突出特征,在大多数情况下都是可见的,我们建议将其直接映射到数字道路网络地形图上,该地形图可以在GIS数据库中随时获得。我们的方法首先检测卫星图像中的道路段,生成道路掩模图像。将小的道路掩码块与栅格化的路网图进行匹配,找到一组可能的道路掩码块位置。在优化平移参数后,每个卫星图像瓦片被粗略地定位在一个路线图上。在第二个精细优化步骤中,进一步优化较小的道路斑块位置。该算法生成一组结合点,这些结合点包含卫星图像像素在局部度量坐标系内的坐标。实验是在斯洛文尼亚一年中不同时期的5张RapidEye图像上进行的。结果表明,所有图像的点的平均误差都在1像素以下,并且在离群像素方面的可靠性很高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Can we date an artist's work from catalogue photographs? Exudate segmentation on retinal atlas space Evaluation of degraded images using adaptive Jensen-Shannon divergence Contrast-based surface saliency Coverage segmentation of thin structures by linear unmixing and local centre of gravity attraction
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1