{"title":"3D image quality assessment using Takagi-Sugeno-Kang fuzzy modele","authors":"D. Dordevic, D. Kukolj, P. Callet","doi":"10.1109/SISY.2014.6923607","DOIUrl":null,"url":null,"abstract":"This paper analyzes and presents impact of two types of the objective image quality assessment measures, no-reference and full-reference measures, on perception quality of 3D image using fuzzy logic estimator namely the Takagi-Sugeno-Kang fuzzy model. Based on the choice of two types of model's inputs, a comparative analysis is performed in this paper. All parameters of the no-reference and full-reference Takagi-Sugeno-Kang models are optimized in accordance to the selected sets mapping criteria of the input objective quality measures to the corresponding Differential Mean Opinion Scores (DMOS).","PeriodicalId":277041,"journal":{"name":"2014 IEEE 12th International Symposium on Intelligent Systems and Informatics (SISY)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE 12th International Symposium on Intelligent Systems and Informatics (SISY)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SISY.2014.6923607","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
This paper analyzes and presents impact of two types of the objective image quality assessment measures, no-reference and full-reference measures, on perception quality of 3D image using fuzzy logic estimator namely the Takagi-Sugeno-Kang fuzzy model. Based on the choice of two types of model's inputs, a comparative analysis is performed in this paper. All parameters of the no-reference and full-reference Takagi-Sugeno-Kang models are optimized in accordance to the selected sets mapping criteria of the input objective quality measures to the corresponding Differential Mean Opinion Scores (DMOS).