Automatic registration of satellite images

Leila Maria Garcia Fonseca, M. H. M. Costa
{"title":"Automatic registration of satellite images","authors":"Leila Maria Garcia Fonseca, M. H. M. Costa","doi":"10.1109/SIGRA.1997.625182","DOIUrl":null,"url":null,"abstract":"Image registration is one of the basic image processing operations in remote sensing. With the increase in the number of images collected every day from different sensors, automated registration of multi-sensor/multi-spectral images has become an important issue. A wide range of registration techniques has been developed for many different types of applications and data. Given the diversity of the data, it is unlikely that a single registration scheme will work satisfactorily for all different applications. A possible solution is to integrate multiple registration algorithms into a rule-based artificial intelligence system, so that appropriate methods for any given set of multisensor data can be automatically selected. The objective of this paper is to present an automatic registration algorithm which has been developed at INPE. It uses a multiresolution analysis procedure based upon the wavelet transform. The procedure is completely automatic and relies on the grey level information content of the images and their local wavelet transform modulus maxima. The algorithm was tested on SPOT and TM images from forest, urban and agricultural areas. In all cases we obtained very encouraging results.","PeriodicalId":445648,"journal":{"name":"Proceedings X Brazilian Symposium on Computer Graphics and Image Processing","volume":"64 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1997-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"81","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings X Brazilian Symposium on Computer Graphics and Image Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SIGRA.1997.625182","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 81

Abstract

Image registration is one of the basic image processing operations in remote sensing. With the increase in the number of images collected every day from different sensors, automated registration of multi-sensor/multi-spectral images has become an important issue. A wide range of registration techniques has been developed for many different types of applications and data. Given the diversity of the data, it is unlikely that a single registration scheme will work satisfactorily for all different applications. A possible solution is to integrate multiple registration algorithms into a rule-based artificial intelligence system, so that appropriate methods for any given set of multisensor data can be automatically selected. The objective of this paper is to present an automatic registration algorithm which has been developed at INPE. It uses a multiresolution analysis procedure based upon the wavelet transform. The procedure is completely automatic and relies on the grey level information content of the images and their local wavelet transform modulus maxima. The algorithm was tested on SPOT and TM images from forest, urban and agricultural areas. In all cases we obtained very encouraging results.
自动配准卫星图像
图像配准是遥感图像处理的基本操作之一。随着每天从不同传感器采集的图像数量的增加,多传感器/多光谱图像的自动配准已经成为一个重要的问题。已经为许多不同类型的应用程序和数据开发了广泛的注册技术。考虑到数据的多样性,单一的注册方案不太可能对所有不同的应用程序都令人满意。一种可能的解决方案是将多种配准算法集成到一个基于规则的人工智能系统中,这样就可以为任何给定的多传感器数据集自动选择合适的方法。本文的目的是介绍一种由INPE开发的自动配准算法。它采用了基于小波变换的多分辨率分析方法。该方法完全自动化,依赖于图像的灰度信息含量及其局部小波变换模极大值。该算法在森林、城市和农业地区的SPOT和TM图像上进行了测试。在所有情况下,我们都取得了非常令人鼓舞的结果。
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:604180095
Book学术官方微信