{"title":"Reduced-reference metric based on the quaternionic wavelet coefficients modeling by information criteria","authors":"A. Traoré, P. Carré, C. Olivier","doi":"10.1109/ICIP.2014.7025105","DOIUrl":null,"url":null,"abstract":"This paper proposes a new reduced-reference metric based on the modeling of Quaternionic Wavelet Transform (QWT) coefficients from Information Criteria (IC). To obtain the reduced-references, we will model the QWT coefficients using probability density functions (pdf) whose parameters are used as reduced-references. IC are proposed in order to build the optimal histograms of the QWT coefficients to get most likely pdf of these. In the mixture model, IC are also used to obtain the number of distribution. From these models, we propose a measure of degradation by comparing probability density functions of the reference image and the distributions of the degraded image of the QWT subbands. We shall demonstrate that one phase of the QWT provides relevant information in the Image Quality Assessment. Tests confirmed the potentiality of this information and showed that the QWT produces a better coefficient of correlation with the Human Visual System than the Discrete Wavelet Transform.","PeriodicalId":6856,"journal":{"name":"2014 IEEE International Conference on Image Processing (ICIP)","volume":"41 1","pages":"526-530"},"PeriodicalIF":0.0000,"publicationDate":"2014-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE International Conference on Image Processing (ICIP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIP.2014.7025105","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
This paper proposes a new reduced-reference metric based on the modeling of Quaternionic Wavelet Transform (QWT) coefficients from Information Criteria (IC). To obtain the reduced-references, we will model the QWT coefficients using probability density functions (pdf) whose parameters are used as reduced-references. IC are proposed in order to build the optimal histograms of the QWT coefficients to get most likely pdf of these. In the mixture model, IC are also used to obtain the number of distribution. From these models, we propose a measure of degradation by comparing probability density functions of the reference image and the distributions of the degraded image of the QWT subbands. We shall demonstrate that one phase of the QWT provides relevant information in the Image Quality Assessment. Tests confirmed the potentiality of this information and showed that the QWT produces a better coefficient of correlation with the Human Visual System than the Discrete Wavelet Transform.