Precise Relative Geometric Correction for Multi-Sensor Satellite Images

S. Ban, Taejung Kim
{"title":"Precise Relative Geometric Correction for Multi-Sensor Satellite Images","authors":"S. Ban, Taejung Kim","doi":"10.5194/isprs-archives-xlviii-2-2024-17-2024","DOIUrl":null,"url":null,"abstract":"Abstract. Rapid progress in satellite technology has led to a noticeable surge in availability of Earth observation satellite images, which are being collected daily from satellites deployed worldwide. However, even with advanced satellite positioning equipment, there are still diverse level of remaining positional errors. This is a hindrance to satellite image utilization. Therefore, positional errors between satellite images must be corrected before utilization. Relative geometric correction of satellite images is a technique that adjusts geometric displacements based on their relative positional relationships in image or object space. In this study, we propose homography-based bundle adjustment for relative geometric correction of multi-sensor satellite images. Our method aims to estimate optimal ground plane on which images are projected and quickly generate result image. For experiments, orthorectified satellite images with various resolutions and georeferencing information were employed as input data. The experiment results showed that the average error, which was initially 4.96 pixels before relative geometric correction, was decreased to 1.73 pixels after applying the proposed method.\n","PeriodicalId":505918,"journal":{"name":"The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences","volume":"25 8","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5194/isprs-archives-xlviii-2-2024-17-2024","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Abstract. Rapid progress in satellite technology has led to a noticeable surge in availability of Earth observation satellite images, which are being collected daily from satellites deployed worldwide. However, even with advanced satellite positioning equipment, there are still diverse level of remaining positional errors. This is a hindrance to satellite image utilization. Therefore, positional errors between satellite images must be corrected before utilization. Relative geometric correction of satellite images is a technique that adjusts geometric displacements based on their relative positional relationships in image or object space. In this study, we propose homography-based bundle adjustment for relative geometric correction of multi-sensor satellite images. Our method aims to estimate optimal ground plane on which images are projected and quickly generate result image. For experiments, orthorectified satellite images with various resolutions and georeferencing information were employed as input data. The experiment results showed that the average error, which was initially 4.96 pixels before relative geometric correction, was decreased to 1.73 pixels after applying the proposed method.
多传感器卫星图像的精确相对几何校正
摘要卫星技术的飞速发展使地球观测卫星图像的可用性明显增加,每天都有部署在世界各地的卫星收集这些图像。然而,即使有了先进的卫星定位设备,仍然存在不同程度的位置误差。这阻碍了卫星图像的利用。因此,卫星图像之间的位置误差必须在使用前得到纠正。卫星图像的相对几何校正是一种根据图像或物体空间中的相对位置关系调整几何位移的技术。在本研究中,我们针对多传感器卫星图像的相对几何校正提出了基于同源性的捆绑调整。我们的方法旨在估计图像投射的最佳地平面,并快速生成结果图像。实验采用了不同分辨率和地理坐标信息的正射卫星图像作为输入数据。实验结果表明,应用所提出的方法后,相对几何校正前的平均误差从最初的 4.96 像素下降到 1.73 像素。
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 求助全文
来源期刊
自引率
0.00%
发文量
0
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信