完整的参考图像质量指标及其性能

K. Kipli, Shankar Krishnan, N. Zamhari, M. Muhammad, S. Masra, Kho Lee Chin, K. Lias
{"title":"完整的参考图像质量指标及其性能","authors":"K. Kipli, Shankar Krishnan, N. Zamhari, M. Muhammad, S. Masra, Kho Lee Chin, K. Lias","doi":"10.1109/CSPA.2011.5759838","DOIUrl":null,"url":null,"abstract":"This paper mainly aims to study the performance of objective assessment methods of image quality. It take into consideration the correlations between each objective assessment and the subjective assessment in order to determine objective test performance. Three objective assessment methods used in this study are the Structural Similarity (SSIM) index, the Peak Signal-to-Noise Ratio (PSNR) and the Mean Squared Error (MSE) calculating algorithm. The resulting data indicate what type of objective assessment was most suitable for which type of impairment imposed upon an image. This is clarified using the Pearson Correlation Coefficient as described in the paper. As an overall, SSIM index had the best correlation characteristics to the subjective assessment, followed by the MSE calculating algorithm. From this study, a better understanding of the requirements for developing an efficient image quality assessment method was gained.","PeriodicalId":282179,"journal":{"name":"2011 IEEE 7th International Colloquium on Signal Processing and its Applications","volume":"12 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":"{\"title\":\"Full reference image quality metrics and their performance\",\"authors\":\"K. Kipli, Shankar Krishnan, N. Zamhari, M. Muhammad, S. Masra, Kho Lee Chin, K. Lias\",\"doi\":\"10.1109/CSPA.2011.5759838\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper mainly aims to study the performance of objective assessment methods of image quality. It take into consideration the correlations between each objective assessment and the subjective assessment in order to determine objective test performance. Three objective assessment methods used in this study are the Structural Similarity (SSIM) index, the Peak Signal-to-Noise Ratio (PSNR) and the Mean Squared Error (MSE) calculating algorithm. The resulting data indicate what type of objective assessment was most suitable for which type of impairment imposed upon an image. This is clarified using the Pearson Correlation Coefficient as described in the paper. As an overall, SSIM index had the best correlation characteristics to the subjective assessment, followed by the MSE calculating algorithm. From this study, a better understanding of the requirements for developing an efficient image quality assessment method was gained.\",\"PeriodicalId\":282179,\"journal\":{\"name\":\"2011 IEEE 7th International Colloquium on Signal Processing and its Applications\",\"volume\":\"12 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-03-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"12\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 IEEE 7th International Colloquium on Signal Processing and its Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CSPA.2011.5759838\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 IEEE 7th International Colloquium on Signal Processing and its Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CSPA.2011.5759838","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 12

摘要

本文主要研究图像质量性能的客观评价方法。它考虑了每个客观评价和主观评价之间的相关性,以确定客观的测试性能。本研究采用的三种客观评价方法分别是结构相似度(SSIM)指数、峰值信噪比(PSNR)和均方误差(MSE)计算算法。结果数据表明哪种类型的客观评估最适合哪种类型的损害强加于图像。这是澄清使用皮尔逊相关系数,如文中所述。总体而言,SSIM指数与主观评价的相关特征最好,其次是MSE计算算法。通过本研究,更好地了解了开发一种有效的图像质量评估方法的需求。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Full reference image quality metrics and their performance
This paper mainly aims to study the performance of objective assessment methods of image quality. It take into consideration the correlations between each objective assessment and the subjective assessment in order to determine objective test performance. Three objective assessment methods used in this study are the Structural Similarity (SSIM) index, the Peak Signal-to-Noise Ratio (PSNR) and the Mean Squared Error (MSE) calculating algorithm. The resulting data indicate what type of objective assessment was most suitable for which type of impairment imposed upon an image. This is clarified using the Pearson Correlation Coefficient as described in the paper. As an overall, SSIM index had the best correlation characteristics to the subjective assessment, followed by the MSE calculating algorithm. From this study, a better understanding of the requirements for developing an efficient image quality assessment method was gained.
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
×
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