{"title":"A method on entropy constrained RVQ design","authors":"Y. Gong, M. Fan, Chien-Min Huang","doi":"10.1109/IECON.1999.822240","DOIUrl":null,"url":null,"abstract":"Entropy constrained residual vector quantization (EC-RVQ) has been shown to be a competitive image compression technique. In this paper, we propose a new algorithm for EC-RVQ design. The main features of the algorithm are: (i) in the encoder update step, we propose a variation of the exhaustive search encoder that significantly speeds up encoding at no expense in terms of the rate-distortion performance; (ii) in the decoder update step, we propose a new method that simultaneously updates the codebooks of all stages; the method is to form and solve a certain least squares problem and we show that both tasks can be done very efficiently; (iii) the Lagrangian of rate-distortion is shown to decrease at every step and thus this guarantees the convergence of the algorithm.","PeriodicalId":378710,"journal":{"name":"IECON'99. Conference Proceedings. 25th Annual Conference of the IEEE Industrial Electronics Society (Cat. No.99CH37029)","volume":"77 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1999-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IECON'99. Conference Proceedings. 25th Annual Conference of the IEEE Industrial Electronics Society (Cat. No.99CH37029)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IECON.1999.822240","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
Entropy constrained residual vector quantization (EC-RVQ) has been shown to be a competitive image compression technique. In this paper, we propose a new algorithm for EC-RVQ design. The main features of the algorithm are: (i) in the encoder update step, we propose a variation of the exhaustive search encoder that significantly speeds up encoding at no expense in terms of the rate-distortion performance; (ii) in the decoder update step, we propose a new method that simultaneously updates the codebooks of all stages; the method is to form and solve a certain least squares problem and we show that both tasks can be done very efficiently; (iii) the Lagrangian of rate-distortion is shown to decrease at every step and thus this guarantees the convergence of the algorithm.