利用对称几何矩评价高斯模糊图像的质量

Chong-Yaw Wee, R. Paramesran, R. Mukundan
{"title":"利用对称几何矩评价高斯模糊图像的质量","authors":"Chong-Yaw Wee, R. Paramesran, R. Mukundan","doi":"10.1109/ICIAP.2007.104","DOIUrl":null,"url":null,"abstract":"A novel objective full-reference image quality assessment metric based on symmetric geometric moments (SGM) is proposed. SGM is used to represent the structural information in the reference and test images. The reference and test images are divided into (8 times 8) blocks and the SGM up to fourth order for each block is computed. SGM of the corresponding blocks of the reference and test images are used to form the correlation index or quality metric of each block. The correlation index of the test image is then obtained by taking the average of all blocks. The performance of the proposed metric is validated through subjective evaluation by comparing with objective methods (PSNR and MSSIM) on a database of 174 Gaussian blurred images. The proposed metric performs better than PSNR and MSSIM by providing larger correlation coefficients and smaller errors after nonlinear regression fitting.","PeriodicalId":118466,"journal":{"name":"14th International Conference on Image Analysis and Processing (ICIAP 2007)","volume":"6 1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"Quality Assessment of Gaussian Blurred Images Using Symmetric Geometric Moments\",\"authors\":\"Chong-Yaw Wee, R. Paramesran, R. Mukundan\",\"doi\":\"10.1109/ICIAP.2007.104\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A novel objective full-reference image quality assessment metric based on symmetric geometric moments (SGM) is proposed. SGM is used to represent the structural information in the reference and test images. The reference and test images are divided into (8 times 8) blocks and the SGM up to fourth order for each block is computed. SGM of the corresponding blocks of the reference and test images are used to form the correlation index or quality metric of each block. The correlation index of the test image is then obtained by taking the average of all blocks. The performance of the proposed metric is validated through subjective evaluation by comparing with objective methods (PSNR and MSSIM) on a database of 174 Gaussian blurred images. The proposed metric performs better than PSNR and MSSIM by providing larger correlation coefficients and smaller errors after nonlinear regression fitting.\",\"PeriodicalId\":118466,\"journal\":{\"name\":\"14th International Conference on Image Analysis and Processing (ICIAP 2007)\",\"volume\":\"6 1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-09-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"14th International Conference on Image Analysis and Processing (ICIAP 2007)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICIAP.2007.104\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"14th International Conference on Image Analysis and Processing (ICIAP 2007)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIAP.2007.104","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9

摘要

提出了一种基于对称几何矩的客观全参考图像质量评价方法。SGM用于表示参考图像和测试图像中的结构信息。将参考图像和测试图像分成(8 × 8)块,计算每个块的最高四阶SGM。使用参考图像和测试图像对应块的SGM形成每个块的相关指标或质量度量。然后对所有块取平均值,得到测试图像的相关指数。通过与客观方法(PSNR和MSSIM)在174张高斯模糊图像数据库上的比较,对所提度量的性能进行了主观评价。该指标在非线性回归拟合后提供了更大的相关系数和更小的误差,优于PSNR和MSSIM。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Quality Assessment of Gaussian Blurred Images Using Symmetric Geometric Moments
A novel objective full-reference image quality assessment metric based on symmetric geometric moments (SGM) is proposed. SGM is used to represent the structural information in the reference and test images. The reference and test images are divided into (8 times 8) blocks and the SGM up to fourth order for each block is computed. SGM of the corresponding blocks of the reference and test images are used to form the correlation index or quality metric of each block. The correlation index of the test image is then obtained by taking the average of all blocks. The performance of the proposed metric is validated through subjective evaluation by comparing with objective methods (PSNR and MSSIM) on a database of 174 Gaussian blurred images. The proposed metric performs better than PSNR and MSSIM by providing larger correlation coefficients and smaller errors after nonlinear regression fitting.
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