## Vector Quantization of Image Subbands: A Survey (1996)

Venue: | IEEE Transactions on Image Processing |

Citations: | 53 - 4 self |

### BibTeX

@ARTICLE{Cosman96vectorquantization,

author = {P. C. Cosman and R.M. Gray and M. Vetterli},

title = {Vector Quantization of Image Subbands: A Survey},

journal = {IEEE Transactions on Image Processing},

year = {1996},

volume = {5},

pages = {202--225}

}

### Years of Citing Articles

### OpenURL

### 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 provides a means of converting the decomposed signal into bits in a manner that takes advantage of remaining inter- and intra-band 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 vector quantization for subband/wavelet transform coefficients. We present a survey of these methods. 1 Introduction Image compression maps an original image into a bit stream suitable for communication over or storage in a digital medium. The number of bits required to represent the coded image should b...