{"title":"基于图像结构特性的质量评价方法","authors":"D. Asatryan, K. Egiazarian","doi":"10.1109/LNLA.2009.5278400","DOIUrl":null,"url":null,"abstract":"In this paper, a new objective quality assessment measure for images is proposed based on statistical structural image analysis using Weibull model and Cramer-von Mises statistics. It is estimated via proximity of parameters of empirical distributions of a gradient magnitude of pixel intensities. Results of numerical experiments demonstrate that the proposed measure is more adequate to perception by human visual system than the usual pixel-by-pixel measures. Unlike other quality assessment measures, a new one can be used on not well-aligned images or on images having different sizes.","PeriodicalId":231766,"journal":{"name":"2009 International Workshop on Local and Non-Local Approximation in Image Processing","volume":"96 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"22","resultStr":"{\"title\":\"Quality assessment measure based on image structural properties\",\"authors\":\"D. Asatryan, K. Egiazarian\",\"doi\":\"10.1109/LNLA.2009.5278400\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, a new objective quality assessment measure for images is proposed based on statistical structural image analysis using Weibull model and Cramer-von Mises statistics. It is estimated via proximity of parameters of empirical distributions of a gradient magnitude of pixel intensities. Results of numerical experiments demonstrate that the proposed measure is more adequate to perception by human visual system than the usual pixel-by-pixel measures. Unlike other quality assessment measures, a new one can be used on not well-aligned images or on images having different sizes.\",\"PeriodicalId\":231766,\"journal\":{\"name\":\"2009 International Workshop on Local and Non-Local Approximation in Image Processing\",\"volume\":\"96 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-10-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"22\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 International Workshop on Local and Non-Local Approximation in Image Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/LNLA.2009.5278400\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 International Workshop on Local and Non-Local Approximation in Image Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/LNLA.2009.5278400","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Quality assessment measure based on image structural properties
In this paper, a new objective quality assessment measure for images is proposed based on statistical structural image analysis using Weibull model and Cramer-von Mises statistics. It is estimated via proximity of parameters of empirical distributions of a gradient magnitude of pixel intensities. Results of numerical experiments demonstrate that the proposed measure is more adequate to perception by human visual system than the usual pixel-by-pixel measures. Unlike other quality assessment measures, a new one can be used on not well-aligned images or on images having different sizes.