{"title":"基于小波图像编码的有限状态点阵矢量量化","authors":"J. Ni, K. Ho, K. Tse","doi":"10.1109/ISCAS.1997.621965","DOIUrl":null,"url":null,"abstract":"It is well known that there exists strong energy correlation between various subbands of a real-world image. A new powerful technique of Finite State Vector Quantization (FSVQ) has been introduced to fully exploit the self-similarity of the image in wavelet domain across different scales. Lattices in R/sup N/ have considerable structure, and hence, Lattice VQ offers the promise of design simplicity and reduced complexity encoding. The combination of FSVQ and LVQ gives rise to the so-called FSLVQ, which is proved to be successful in exploiting the energy correlation across scales and is simple enough in implementation.","PeriodicalId":68559,"journal":{"name":"电路与系统学报","volume":"47 1","pages":"1137-1140 vol.2"},"PeriodicalIF":0.0000,"publicationDate":"1997-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Finite state lattice vector quantization for wavelet-based image coding\",\"authors\":\"J. Ni, K. Ho, K. Tse\",\"doi\":\"10.1109/ISCAS.1997.621965\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"It is well known that there exists strong energy correlation between various subbands of a real-world image. A new powerful technique of Finite State Vector Quantization (FSVQ) has been introduced to fully exploit the self-similarity of the image in wavelet domain across different scales. Lattices in R/sup N/ have considerable structure, and hence, Lattice VQ offers the promise of design simplicity and reduced complexity encoding. The combination of FSVQ and LVQ gives rise to the so-called FSLVQ, which is proved to be successful in exploiting the energy correlation across scales and is simple enough in implementation.\",\"PeriodicalId\":68559,\"journal\":{\"name\":\"电路与系统学报\",\"volume\":\"47 1\",\"pages\":\"1137-1140 vol.2\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1997-06-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"电路与系统学报\",\"FirstCategoryId\":\"1093\",\"ListUrlMain\":\"https://doi.org/10.1109/ISCAS.1997.621965\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"电路与系统学报","FirstCategoryId":"1093","ListUrlMain":"https://doi.org/10.1109/ISCAS.1997.621965","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Finite state lattice vector quantization for wavelet-based image coding
It is well known that there exists strong energy correlation between various subbands of a real-world image. A new powerful technique of Finite State Vector Quantization (FSVQ) has been introduced to fully exploit the self-similarity of the image in wavelet domain across different scales. Lattices in R/sup N/ have considerable structure, and hence, Lattice VQ offers the promise of design simplicity and reduced complexity encoding. The combination of FSVQ and LVQ gives rise to the so-called FSLVQ, which is proved to be successful in exploiting the energy correlation across scales and is simple enough in implementation.