Fast no-reference image sharpness measure for blurred images in discrete cosine transform domain

K. De, V. Masilamani
{"title":"Fast no-reference image sharpness measure for blurred images in discrete cosine transform domain","authors":"K. De, V. Masilamani","doi":"10.1109/TECHSYM.2016.7872692","DOIUrl":null,"url":null,"abstract":"Researchers working in the field of image quality assessment are constantly developing algorithms for assessing the quality of a given image. This is a very challenging task as the given image may be affected by different types of distortions. One of the most common distortions is image blurring. In this paper, we propose a no-reference image quality assessment algorithm to assess the quality of images corrupted by blurring in Discrete Cosine Transform domain. The proposed algorithm works faster than the state of the art algorithms for the same problem, and the score computed by the algorithm has more correlation with the human opinion score than existing methods which means that the proposed image sharpness measure mimicks the human visual system closely.","PeriodicalId":403350,"journal":{"name":"2016 IEEE Students’ Technology Symposium (TechSym)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE Students’ Technology Symposium (TechSym)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TECHSYM.2016.7872692","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7

Abstract

Researchers working in the field of image quality assessment are constantly developing algorithms for assessing the quality of a given image. This is a very challenging task as the given image may be affected by different types of distortions. One of the most common distortions is image blurring. In this paper, we propose a no-reference image quality assessment algorithm to assess the quality of images corrupted by blurring in Discrete Cosine Transform domain. The proposed algorithm works faster than the state of the art algorithms for the same problem, and the score computed by the algorithm has more correlation with the human opinion score than existing methods which means that the proposed image sharpness measure mimicks the human visual system closely.
离散余弦变换域中模糊图像的快速无参考图像清晰度测量
图像质量评估领域的研究人员一直在不断开发用于评估给定图像质量的算法。这是一项非常具有挑战性的任务,因为给定的图像可能受到不同类型的扭曲的影响。最常见的失真之一是图像模糊。在本文中,我们提出了一种无参考图像质量评估算法来评估离散余弦变换域中因模糊而损坏的图像质量。对于相同的问题,该算法的工作速度比现有的算法要快,并且与现有的方法相比,该算法计算的分数与人类的意见分数有更大的相关性,这意味着所提出的图像清晰度测量方法更接近人类的视觉系统。
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