International Journal of Applied Mathematics and Machine Learning

Xiuming Sun, Weina Wu, P. Geng, Lin Lu
{"title":"International Journal of Applied Mathematics and Machine Learning","authors":"Xiuming Sun, Weina Wu, P. Geng, Lin Lu","doi":"10.18642/ijamml_7100122215","DOIUrl":null,"url":null,"abstract":"In order to achieve the multi-focus image fusion task, a sparse representation method based on quaternion for multi-focus image fusion is proposed in this paper. Firstly, the RGB color information of each pixel in the color image is represented by quaternion based on the relevant knowledge of computational mathematics, and the color image pixel is processed as a whole vector to maintain the relevant information between the three color channels. Secondly, the dictionary represented by quaternion and the sparse coefficient represented by quaternion are obtained by using the our proposed sparse representation model. Thirdly, the coefficient fusion is carried out by using the “max-L1” rule. Finally, the fused sparse coefficient and dictionary are used for image reconstruction to obtain the quaternion fused image, which is then converted into RGB color multi-focus fused image. Our method belongs to computational mathematics, and uses the relevant knowledge in the field of computational mathematics to help us carry out the experiment. The experimental results show that the method has achieved good results in visual quality and objective evaluation.","PeriodicalId":405830,"journal":{"name":"International Journal of Applied Mathematics and Machine Learning","volume":"43 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Applied Mathematics and Machine Learning","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.18642/ijamml_7100122215","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

In order to achieve the multi-focus image fusion task, a sparse representation method based on quaternion for multi-focus image fusion is proposed in this paper. Firstly, the RGB color information of each pixel in the color image is represented by quaternion based on the relevant knowledge of computational mathematics, and the color image pixel is processed as a whole vector to maintain the relevant information between the three color channels. Secondly, the dictionary represented by quaternion and the sparse coefficient represented by quaternion are obtained by using the our proposed sparse representation model. Thirdly, the coefficient fusion is carried out by using the “max-L1” rule. Finally, the fused sparse coefficient and dictionary are used for image reconstruction to obtain the quaternion fused image, which is then converted into RGB color multi-focus fused image. Our method belongs to computational mathematics, and uses the relevant knowledge in the field of computational mathematics to help us carry out the experiment. The experimental results show that the method has achieved good results in visual quality and objective evaluation.
国际应用数学与机器学习杂志
为了实现多焦点图像融合任务,本文提出了一种基于四元数的稀疏表示多焦点图像融合方法。首先,基于计算数学的相关知识,将彩色图像中每个像素的RGB颜色信息用四元数表示,并将彩色图像像素作为一个整体矢量进行处理,保持三个颜色通道之间的相关信息。其次,利用本文提出的稀疏表示模型,得到四元数表示的字典和四元数表示的稀疏系数。第三,采用“max-L1”规则进行系数融合。最后,利用融合稀疏系数和字典进行图像重建,得到四元数融合图像,并将其转换为RGB彩色多焦点融合图像。我们的方法属于计算数学,使用计算数学领域的相关知识来帮助我们进行实验。实验结果表明,该方法在视觉质量和客观评价方面取得了较好的效果。
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