{"title":"Comparison of Super-Resolution Algorithms Using Image Quality Measures","authors":"I. Bégin, F. Ferrie","doi":"10.1109/CRV.2006.23","DOIUrl":null,"url":null,"abstract":"This paper presents comparisons of two learning-based super-resolution algorithms as well as standard interpolation methods. To allow quality assessment of results, a comparison of a variety of image quality measures is also performed. Results show that a MRF-based super-resolution algorithm improves a previously interpolated image. The estimated degree of improvement varies both according to the quality measure chosen for the comparison as well as the image class.","PeriodicalId":369170,"journal":{"name":"The 3rd Canadian Conference on Computer and Robot Vision (CRV'06)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"30","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"The 3rd Canadian Conference on Computer and Robot Vision (CRV'06)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CRV.2006.23","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 30
Abstract
This paper presents comparisons of two learning-based super-resolution algorithms as well as standard interpolation methods. To allow quality assessment of results, a comparison of a variety of image quality measures is also performed. Results show that a MRF-based super-resolution algorithm improves a previously interpolated image. The estimated degree of improvement varies both according to the quality measure chosen for the comparison as well as the image class.