{"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}
引用次数: 2
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.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
