Literature DB >> 18285108

Vector quantization of image subbands: a survey.

P C Cosman1, R M Gray, M Vetterli.   

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.

Entities:  

Year:  1996        PMID: 18285108     DOI: 10.1109/83.480760

Source DB:  PubMed          Journal:  IEEE Trans Image Process        ISSN: 1057-7149            Impact factor:   10.856


  1 in total

1.  Medical Image Retrieval Using Vector Quantization and Fuzzy S-tree.

Authors:  Jana Nowaková; Michal Prílepok; Václav Snášel
Journal:  J Med Syst       Date:  2016-12-15       Impact factor: 4.460

  1 in total

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