{"title":"Dual set arithmetic coding and its applications to image coding","authors":"B. Zhu, E. Yang, A. Tewfik","doi":"10.5281/ZENODO.36231","DOIUrl":null,"url":null,"abstract":"Arithmetic coding is usually implemented in fixed precision. Such an implementation cannot efficiently code sources, such as image coding algorithms, that locally produce a small fraction of a large alphabet of symbols. In this paper, we propose a novel approach to overcome this inefficiency. The proposed algorithm uses dual symbol sets: a primary symbol set that contains the symbols that have occurred in the recent past and a secondary symbol set that contains all other symbols. Both sets are dynamically adapted to the local statistics. We summarize an analysis of the proposed approach and describe the results that we have obtained by applying it to images.","PeriodicalId":282153,"journal":{"name":"1996 8th European Signal Processing Conference (EUSIPCO 1996)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1996-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"1996 8th European Signal Processing Conference (EUSIPCO 1996)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5281/ZENODO.36231","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
Arithmetic coding is usually implemented in fixed precision. Such an implementation cannot efficiently code sources, such as image coding algorithms, that locally produce a small fraction of a large alphabet of symbols. In this paper, we propose a novel approach to overcome this inefficiency. The proposed algorithm uses dual symbol sets: a primary symbol set that contains the symbols that have occurred in the recent past and a secondary symbol set that contains all other symbols. Both sets are dynamically adapted to the local statistics. We summarize an analysis of the proposed approach and describe the results that we have obtained by applying it to images.