Suhaila Abdalla Awad Abras, Hazeifa Adam Abd Alshafy
{"title":"No-Reference Framework for Image Quality Assessment","authors":"Suhaila Abdalla Awad Abras, Hazeifa Adam Abd Alshafy","doi":"10.53332/kuej.v10i1.931","DOIUrl":null,"url":null,"abstract":"The technological advances in computer and communication devices have been an important factor in the appearance for the applications of visual communication. Image quality assessment is one of the pillars for these applications. It is a measure to assess the quality of images. There are many degradations in image quality that occur during the reproduction and transmission of the image. This paper aims to introduce a framework of No-Reference Image Quality Assessment. The framework provides a general estimation for three types of image distortions which are sharpness, blackness, and noisiness. Based on this framework, experiments have been conducted by the use of two datasets (LIVE database, CSIQ database). The results of the experiments have shown that we have introduced a more precise framework of No-Reference Image Quality Assessment.","PeriodicalId":23461,"journal":{"name":"University of Khartoum Engineering Journal","volume":"8 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"University of Khartoum Engineering Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.53332/kuej.v10i1.931","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The technological advances in computer and communication devices have been an important factor in the appearance for the applications of visual communication. Image quality assessment is one of the pillars for these applications. It is a measure to assess the quality of images. There are many degradations in image quality that occur during the reproduction and transmission of the image. This paper aims to introduce a framework of No-Reference Image Quality Assessment. The framework provides a general estimation for three types of image distortions which are sharpness, blackness, and noisiness. Based on this framework, experiments have been conducted by the use of two datasets (LIVE database, CSIQ database). The results of the experiments have shown that we have introduced a more precise framework of No-Reference Image Quality Assessment.