{"title":"二值矢量量化器优化设计的新算法","authors":"Xiaolin Wu, Yonggang Fang","doi":"10.1109/DCC.1995.515503","DOIUrl":null,"url":null,"abstract":"New algorithms are proposed for designing optimal binary vector quantizers. These algorithms aim to avoid the problem of the generalized Lloyd method of easily getting trapped into a poor local minimum. To improve the subjective quality of vector-quantized binary images, a constrained optimal binary VQ framework is proposed. Within this framework, the optimal VQ design can be done via an interesting use of linear codes.","PeriodicalId":107017,"journal":{"name":"Proceedings DCC '95 Data Compression Conference","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1995-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"New algorithms for optimal binary vector quantizer design\",\"authors\":\"Xiaolin Wu, Yonggang Fang\",\"doi\":\"10.1109/DCC.1995.515503\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"New algorithms are proposed for designing optimal binary vector quantizers. These algorithms aim to avoid the problem of the generalized Lloyd method of easily getting trapped into a poor local minimum. To improve the subjective quality of vector-quantized binary images, a constrained optimal binary VQ framework is proposed. Within this framework, the optimal VQ design can be done via an interesting use of linear codes.\",\"PeriodicalId\":107017,\"journal\":{\"name\":\"Proceedings DCC '95 Data Compression Conference\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1995-03-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings DCC '95 Data Compression Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/DCC.1995.515503\",\"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 '95 Data Compression Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DCC.1995.515503","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
New algorithms for optimal binary vector quantizer design
New algorithms are proposed for designing optimal binary vector quantizers. These algorithms aim to avoid the problem of the generalized Lloyd method of easily getting trapped into a poor local minimum. To improve the subjective quality of vector-quantized binary images, a constrained optimal binary VQ framework is proposed. Within this framework, the optimal VQ design can be done via an interesting use of linear codes.