Vector quantization of image subbands: A survey

被引:99
作者
Cosman, PC
Gray, RM
Vetterli, M
机构
[1] STANFORD UNIV,DEPT ELECT ENGN,STANFORD,CA 94305
[2] UNIV CALIF BERKELEY,DEPT ELECT ENGN & COMP SCI,BERKELEY,CA 94720
基金
美国国家科学基金会;
关键词
D O I
10.1109/83.480760
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Subband and wavelet decompositions are powerful tools in image coding because of their decorrelating effects on image pixels, the concentration of energy in a few coefficients, their multirate/multiresolution framework, and their frequency splitting, which allows for efficient coding matched to the statistics of each frequency band and to the characteristics of the human visual system, Vector quantization (VQ) provides a means of converting the decomposed signal into bits in a manner that takes advantage of remaining inter and intraband correlation as well as of the more flexible partitions of higher dimensional vector spaces, Since 1988, a growing body of research has examined the use of VQ for subband/wavelet transform coefficients, We present a survey of these methods.
引用
收藏
页码:202 / 225
页数:24
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