{"title":"一类扩展的golomb型码族的自适应策略","authors":"G. Seroussi, M. Weinberger","doi":"10.1109/DCC.1997.581993","DOIUrl":null,"url":null,"abstract":"Off-centered, two-sided geometric distributions of the integers are often encountered in lossless image compression applications, as probabilistic models for prediction residuals. Based on a recent characterization of the family of optimal prefix codes for these distributions, which is an extension of the Golomb (1966) codes, we investigate adaptive strategies for their symbol-by-symbol prefix coding, as opposed to arithmetic coding. Our strategies allow for adaptive coding of prediction residuals at very low complexity. They provide a theoretical framework for the heuristic approximations frequently used when modifying the Golomb code, originally designed for one-sided geometric distributions of non-negative integers, so as to apply to the encoding of any integer.","PeriodicalId":403990,"journal":{"name":"Proceedings DCC '97. Data Compression Conference","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1997-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"33","resultStr":"{\"title\":\"On adaptive strategies for an extended family of Golomb-type codes\",\"authors\":\"G. Seroussi, M. Weinberger\",\"doi\":\"10.1109/DCC.1997.581993\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Off-centered, two-sided geometric distributions of the integers are often encountered in lossless image compression applications, as probabilistic models for prediction residuals. Based on a recent characterization of the family of optimal prefix codes for these distributions, which is an extension of the Golomb (1966) codes, we investigate adaptive strategies for their symbol-by-symbol prefix coding, as opposed to arithmetic coding. Our strategies allow for adaptive coding of prediction residuals at very low complexity. They provide a theoretical framework for the heuristic approximations frequently used when modifying the Golomb code, originally designed for one-sided geometric distributions of non-negative integers, so as to apply to the encoding of any integer.\",\"PeriodicalId\":403990,\"journal\":{\"name\":\"Proceedings DCC '97. Data Compression Conference\",\"volume\":\"6 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1997-03-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"33\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings DCC '97. Data Compression Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/DCC.1997.581993\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings DCC '97. Data Compression Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DCC.1997.581993","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
On adaptive strategies for an extended family of Golomb-type codes
Off-centered, two-sided geometric distributions of the integers are often encountered in lossless image compression applications, as probabilistic models for prediction residuals. Based on a recent characterization of the family of optimal prefix codes for these distributions, which is an extension of the Golomb (1966) codes, we investigate adaptive strategies for their symbol-by-symbol prefix coding, as opposed to arithmetic coding. Our strategies allow for adaptive coding of prediction residuals at very low complexity. They provide a theoretical framework for the heuristic approximations frequently used when modifying the Golomb code, originally designed for one-sided geometric distributions of non-negative integers, so as to apply to the encoding of any integer.