Joint image registration and super-resolution based on combinational coefficient matrix

H. Rezayi, S. Seyedin
{"title":"Joint image registration and super-resolution based on combinational coefficient matrix","authors":"H. Rezayi, S. Seyedin","doi":"10.1109/PRIA.2015.7161636","DOIUrl":null,"url":null,"abstract":"In this paper we propose a new joint image registration (IR) and super-resolution (SR) method by combining the three principal operations of warping, blurring and down-sampling. Unlike previous methods, we neither calculate the Jacobian matrix numerically nor derive the Jacobian matrix by treating the three principal operations separately. We develop a new approach to derive the Jacobian matrix analytically from the combination of the three principal operations. Experimental results show that our method has better Peak Signal-to-Noise Ratio (PSNR) than the recently proposed Tian's joint method of IR and SR. Computational complexity also has been decreased in our proposed method.","PeriodicalId":163817,"journal":{"name":"2015 2nd International Conference on Pattern Recognition and Image Analysis (IPRIA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 2nd International Conference on Pattern Recognition and Image Analysis (IPRIA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PRIA.2015.7161636","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5

Abstract

In this paper we propose a new joint image registration (IR) and super-resolution (SR) method by combining the three principal operations of warping, blurring and down-sampling. Unlike previous methods, we neither calculate the Jacobian matrix numerically nor derive the Jacobian matrix by treating the three principal operations separately. We develop a new approach to derive the Jacobian matrix analytically from the combination of the three principal operations. Experimental results show that our method has better Peak Signal-to-Noise Ratio (PSNR) than the recently proposed Tian's joint method of IR and SR. Computational complexity also has been decreased in our proposed method.
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
基于组合系数矩阵的联合图像配准与超分辨率
本文提出了一种结合扭曲、模糊和降采样三种主要操作的图像配准和超分辨率联合配准方法。与以前的方法不同,我们既不通过数值计算雅可比矩阵,也不通过分别处理三个主要操作来推导雅可比矩阵。本文提出了一种由三种主运算组合解析导出雅可比矩阵的新方法。实验结果表明,该方法比Tian的IR和sr联合方法具有更好的峰值信噪比(PSNR),并降低了计算复杂度。
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
Retinal vessel segmentation using system fuzzy and DBSCAN algorithm A new robust semi-blind image watermarking based on block classification and visual cryptography A binary-segmentation algorithm based on shearlet transform and eigenvectors CGSR features: Toward RGB-D image matching using color gradient description of geometrically stable regions Facial expression recognition using high order directional derivative local binary patterns
×
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