{"title":"NRPSNR: No-Reference Peak Signal-to-Noise Ratio for JPEG2000","authors":"J. Moreno, Beatriz Jaime, C. Fernandez-Maloigne","doi":"10.1109/DCC.2013.117","DOIUrl":null,"url":null,"abstract":"The aim of this work is to define a no-referenced perceptual image quality estimator applying the perceptual concepts of the Chromatic Induction Model. The approach consists in comparing the received image, presumably degraded, against the perceptual versions (different distances) of this image degraded by means of a Model of Chromatic Induction, which uses some of the human visual system properties. Also we compare our model with a original estimator in image quality assessment, PSNR. Results are highly correlated with the ones obtained by PSNR for image (99.32% Lenna and 96.95% for image Baboon), but this proposal does not need an original image or a reference one in order to give an estimation of the quality of the degraded image.","PeriodicalId":388717,"journal":{"name":"2013 Data Compression Conference","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 Data Compression Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DCC.2013.117","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 aim of this work is to define a no-referenced perceptual image quality estimator applying the perceptual concepts of the Chromatic Induction Model. The approach consists in comparing the received image, presumably degraded, against the perceptual versions (different distances) of this image degraded by means of a Model of Chromatic Induction, which uses some of the human visual system properties. Also we compare our model with a original estimator in image quality assessment, PSNR. Results are highly correlated with the ones obtained by PSNR for image (99.32% Lenna and 96.95% for image Baboon), but this proposal does not need an original image or a reference one in order to give an estimation of the quality of the degraded image.
这项工作的目的是定义一个无参考的感知图像质量估计应用着色感应模型的感知概念。该方法包括将接收到的图像(可能已经降级)与通过使用一些人类视觉系统属性的色彩感应模型(Model of Chromatic Induction)降级的图像的感知版本(不同距离)进行比较。此外，我们还将我们的模型与原始估计器在图像质量评估PSNR方面进行了比较。结果与图像的PSNR (Lenna为99.32%，狒狒为96.95%)的结果高度相关，但该方案不需要原始图像或参考图像就可以对退化图像的质量进行估计。
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