{"title":"On joint distribution modeling in distributed video coding systems","authors":"Y. Priziment, D. Malah","doi":"10.1109/MMSP.2010.5662037","DOIUrl":null,"url":null,"abstract":"Performance of a distributed video coding system depends, to a large extent, on the accuracy of joint source and side information distribution modeling. In this work we first examine a family of stationary joint distribution models. As one of our findings, we propose to use the double-Gamma model as an alternative to the widely adopted Laplace model, due to its superior performance. In addition, we suggest a new spatially adaptive model, which enables to follow the spatially varying joint statistics of the source and side information. We present two methods, class-based and neighborhood-based, for estimation of the spatially varying model parameters. We then show how the obtained pixel domain model can be used in the transform domain to facilitate utilization of frame spatial redundancy. Integration of the proposed models into a distributed video coding system resulted in improved performance.","PeriodicalId":105774,"journal":{"name":"2010 IEEE International Workshop on Multimedia Signal Processing","volume":"130 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 IEEE International Workshop on Multimedia Signal Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MMSP.2010.5662037","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Performance of a distributed video coding system depends, to a large extent, on the accuracy of joint source and side information distribution modeling. In this work we first examine a family of stationary joint distribution models. As one of our findings, we propose to use the double-Gamma model as an alternative to the widely adopted Laplace model, due to its superior performance. In addition, we suggest a new spatially adaptive model, which enables to follow the spatially varying joint statistics of the source and side information. We present two methods, class-based and neighborhood-based, for estimation of the spatially varying model parameters. We then show how the obtained pixel domain model can be used in the transform domain to facilitate utilization of frame spatial redundancy. Integration of the proposed models into a distributed video coding system resulted in improved performance.