Meng Lei, Falei Luo, Xinfeng Zhang, Shanshe Wang, Siwei Ma
{"title":"Two-Step Progressive Intra Prediction For Versatile Video Coding","authors":"Meng Lei, Falei Luo, Xinfeng Zhang, Shanshe Wang, Siwei Ma","doi":"10.1109/ICIP40778.2020.9190915","DOIUrl":null,"url":null,"abstract":"In traditional intra prediction, nearest reference samples are utilized to generate the prediction block. Although more directional intra modes and reference lines have been utilized, encoders could not predict complex content with only the 10-cal reference samples efficiently. To address this issue, a twostep progressive prediction method combining local and nonlocal information is proposed. The non-local information can be obtained through template matching based prediction, and the local information can be derived by the high frequency coefficients from the first prediction step. Experimental results show that the proposed method can achieve 0.87% BD-rate reduction in VTM-7.0. In particular, the method is of significant advantages over prediction schemes using only non-local information.","PeriodicalId":405734,"journal":{"name":"2020 IEEE International Conference on Image Processing (ICIP)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2020-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE International Conference on Image Processing (ICIP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIP40778.2020.9190915","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
In traditional intra prediction, nearest reference samples are utilized to generate the prediction block. Although more directional intra modes and reference lines have been utilized, encoders could not predict complex content with only the 10-cal reference samples efficiently. To address this issue, a twostep progressive prediction method combining local and nonlocal information is proposed. The non-local information can be obtained through template matching based prediction, and the local information can be derived by the high frequency coefficients from the first prediction step. Experimental results show that the proposed method can achieve 0.87% BD-rate reduction in VTM-7.0. In particular, the method is of significant advantages over prediction schemes using only non-local information.