Hyperspectral and panchromatic image fusion based on CNMF

Tianyu Mu, Rencan Nie, Chaozhen Ma, Jie Liu
{"title":"Hyperspectral and panchromatic image fusion based on CNMF","authors":"Tianyu Mu, Rencan Nie, Chaozhen Ma, Jie Liu","doi":"10.1109/CTISC52352.2021.00060","DOIUrl":null,"url":null,"abstract":"Hyperspectral images contain rich spectral features, but the spatial resolution of hyperspectral images is low, so image fusion technology in the same scene plays an essential role in satellite imaging. The commonly used method now is to transfer the spectral information in the hyperspectral image to the panchromatic image, but many algorithms cannot avoid spectral distortion. Based on the coupled non-negative matrix decomposition (CNMF) algorithm, a spectral constraint regularization term is introduced to avoid spectral distortion and maintain spectral integrity. The experimental results were compared with the other four most advanced methods, this method has obvious advantages in terms of visual effects and evaluation indicators.","PeriodicalId":268378,"journal":{"name":"2021 3rd International Conference on Advances in Computer Technology, Information Science and Communication (CTISC)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 3rd International Conference on Advances in Computer Technology, Information Science and Communication (CTISC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CTISC52352.2021.00060","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

Hyperspectral images contain rich spectral features, but the spatial resolution of hyperspectral images is low, so image fusion technology in the same scene plays an essential role in satellite imaging. The commonly used method now is to transfer the spectral information in the hyperspectral image to the panchromatic image, but many algorithms cannot avoid spectral distortion. Based on the coupled non-negative matrix decomposition (CNMF) algorithm, a spectral constraint regularization term is introduced to avoid spectral distortion and maintain spectral integrity. The experimental results were compared with the other four most advanced methods, this method has obvious advantages in terms of visual effects and evaluation indicators.
基于CNMF的高光谱与全色图像融合
高光谱图像包含丰富的光谱特征,但高光谱图像的空间分辨率较低,因此同一场景下的图像融合技术在卫星成像中起着至关重要的作用。目前常用的方法是将高光谱图像中的光谱信息转移到全色图像中,但许多算法无法避免光谱失真。在耦合非负矩阵分解(CNMF)算法的基础上,引入频谱约束正则化项,避免频谱失真,保持频谱完整性。实验结果与其他四种最先进的方法进行了比较,该方法在视觉效果和评价指标方面具有明显的优势。
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