{"title":"流式分段常数模型","authors":"Paul J. Ausbeck","doi":"10.1109/DCC.1999.755670","DOIUrl":null,"url":null,"abstract":"The piecewise-constant image model (PWC) is remarkably effective for compressing palette images. This paper discloses a new streaming version of PWC that retains the excellent compression efficiency of the original algorithm while dramatically enhancing compression performance. Further, compression throughput is made more constant, making it possible to code sparse images very quickly.","PeriodicalId":103598,"journal":{"name":"Proceedings DCC'99 Data Compression Conference (Cat. No. PR00096)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1999-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"19","resultStr":"{\"title\":\"A streaming piecewise-constant model\",\"authors\":\"Paul J. Ausbeck\",\"doi\":\"10.1109/DCC.1999.755670\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The piecewise-constant image model (PWC) is remarkably effective for compressing palette images. This paper discloses a new streaming version of PWC that retains the excellent compression efficiency of the original algorithm while dramatically enhancing compression performance. Further, compression throughput is made more constant, making it possible to code sparse images very quickly.\",\"PeriodicalId\":103598,\"journal\":{\"name\":\"Proceedings DCC'99 Data Compression Conference (Cat. No. PR00096)\",\"volume\":\"32 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1999-03-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"19\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings DCC'99 Data Compression Conference (Cat. No. PR00096)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/DCC.1999.755670\",\"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'99 Data Compression Conference (Cat. No. PR00096)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DCC.1999.755670","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The piecewise-constant image model (PWC) is remarkably effective for compressing palette images. This paper discloses a new streaming version of PWC that retains the excellent compression efficiency of the original algorithm while dramatically enhancing compression performance. Further, compression throughput is made more constant, making it possible to code sparse images very quickly.
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