一种基于特征和强度的SSIM优化混合图像配准技术

T. Kumari, Vikrant Guleria, P. Syal, A. Aggarwal
{"title":"一种基于特征和强度的SSIM优化混合图像配准技术","authors":"T. Kumari, Vikrant Guleria, P. Syal, A. Aggarwal","doi":"10.1109/CCGE50943.2021.9776407","DOIUrl":null,"url":null,"abstract":"The hybrid image registration method is proposed to align two images based on the features or corresponding intensity information present in the images. The motivation behind the proposed work is that there is no one method or algorithm available that is suitable for any kind of images. SURF feature-based algorithm is used to extract, match, and describe the features present in the image. $1+1$ evolutionary and regular step gradient descent algorithm is used for intensity information present in the images. The performance parameter to evaluate registration accuracy used in the proposed work are SSIM, MSE, PSNR, IQI, PCC and SSD which shows improvement in prior and post registration results.","PeriodicalId":130452,"journal":{"name":"2021 International Conference on Computing, Communication and Green Engineering (CCGE)","volume":"76 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"A Feature Cum Intensity Based SSIM Optimised Hybrid Image Registration Technique\",\"authors\":\"T. Kumari, Vikrant Guleria, P. Syal, A. Aggarwal\",\"doi\":\"10.1109/CCGE50943.2021.9776407\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The hybrid image registration method is proposed to align two images based on the features or corresponding intensity information present in the images. The motivation behind the proposed work is that there is no one method or algorithm available that is suitable for any kind of images. SURF feature-based algorithm is used to extract, match, and describe the features present in the image. $1+1$ evolutionary and regular step gradient descent algorithm is used for intensity information present in the images. The performance parameter to evaluate registration accuracy used in the proposed work are SSIM, MSE, PSNR, IQI, PCC and SSD which shows improvement in prior and post registration results.\",\"PeriodicalId\":130452,\"journal\":{\"name\":\"2021 International Conference on Computing, Communication and Green Engineering (CCGE)\",\"volume\":\"76 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-09-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 International Conference on Computing, Communication and Green Engineering (CCGE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CCGE50943.2021.9776407\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 International Conference on Computing, Communication and Green Engineering (CCGE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCGE50943.2021.9776407","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

摘要

提出了基于图像中存在的特征或相应的强度信息对两幅图像进行对齐的混合图像配准方法。提出的工作背后的动机是,没有一种方法或算法适用于任何类型的图像。基于SURF特征的算法用于提取、匹配和描述图像中存在的特征。对图像中存在的强度信息采用$1+1$进化和规则阶跃梯度下降算法。本文采用SSIM、MSE、PSNR、IQI、PCC和SSD作为评价配准精度的性能参数,表明配准前后的配准效果都有所改善。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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
A Feature Cum Intensity Based SSIM Optimised Hybrid Image Registration Technique
The hybrid image registration method is proposed to align two images based on the features or corresponding intensity information present in the images. The motivation behind the proposed work is that there is no one method or algorithm available that is suitable for any kind of images. SURF feature-based algorithm is used to extract, match, and describe the features present in the image. $1+1$ evolutionary and regular step gradient descent algorithm is used for intensity information present in the images. The performance parameter to evaluate registration accuracy used in the proposed work are SSIM, MSE, PSNR, IQI, PCC and SSD which shows improvement in prior and post registration results.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Stock Market Analysis using Time Series Data Analytics Techniques [Agendas] Irrigation to Smart Irrigation and Tube Well Users A Feature Cum Intensity Based SSIM Optimised Hybrid Image Registration Technique Flood Level Control and Management Using Instrumentation and Control
×
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