Vector Quantization I:Structure and Performance

  • Allen Gersho
  • Robert M. Gray
Part of the The Springer International Series in Engineering and Computer Science book series (SECS, volume 159)


Vector quantization (VQ) is a generalization of scalar quantization to the quantization of a vector, an ordered set of real numbers. The jump from one dimension to multiple dimensions is a major step and allows a wealth of new ideas, concepts, techniques, and applications to arise that often have no counterpart in the simple case of scalar quantization. While scalar quantization is used primarily for analog-to-digital conversion, VQ is used with sophisticated digital signal processing, where in most cases the input signal already has some form of digital representation and the desired output is a compressed version of the original signal. VQ is usually, but not exclusively, used for the purpose of data compression. Nevertheless, there are interesting parallels with scalar quantization and many of the structural models and analytical and design techniques used in VQ are natural generalizations of the scalar case.


Input Vector Near Neighbor Vector Quantization Voronoi Cell Scalar Quantization 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer Science+Business Media New York 1992

Authors and Affiliations

  • Allen Gersho
    • 1
  • Robert M. Gray
    • 2
  1. 1.University of CaliforniaSanta BarbaraUSA
  2. 2.Stanford UniversityUSA

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