DocumentCode :
1213659
Title :
Vector quantization of image subbands: a survey
Author :
Cosman, Pamela C. ; Gray, Robert M. ; Vetterli, Martin
Author_Institution :
Dept. of Electr. & Comput. Eng., California Univ., San Diego, La Jolla, CA, USA
Volume :
5
Issue :
2
fYear :
1996
fDate :
2/1/1996 12:00:00 AM
Firstpage :
202
Lastpage :
225
Abstract :
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
Keywords :
image coding; transform coding; vector quantisation; wavelet transforms; decomposed signal; decorrelating effects; energy concentration; frequency band; frequency splitting; higher dimensional vector spaces; human visual system; image coding; image pixels; image subbands; interband correlation; intraband correlation; multirate framework; multiresolution framework; review; statistics; vector quantization; wavelet decompositions; Decorrelation; Energy resolution; Frequency; Humans; Image coding; Image resolution; Pixel; Signal resolution; Statistics; Vector quantization;
fLanguage :
English
Journal_Title :
Image Processing, IEEE Transactions on
Publisher :
ieee
ISSN :
1057-7149
Type :
jour
DOI :
10.1109/83.480760
Filename :
480760
Link To Document :
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