A mean-removed variation of weighted universal vector quantization for image coding
- 31 December 2002
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- p. 302-309
- https://doi.org/10.1109/dcc.1993.253119
Abstract
Weighted universal vector quantization uses traditional codeword design techniques to design locally optimal multi-codebook systems. Application of this technique to a sequence of medical images produces a 10.3 dB improvement over standard full search vector quantization followed by entropy coding at the cost of increased complexity. In this proposed variation each codebook in the system is given a mean or `prediction' value which is subtracted from all supervectors that map to the given codebook. The chosen codebook's codewords are then used to encode the resulting residuals. Application of the mean-removed system to the medical data set achieves up to 0.5 dB improvement at no rate expense Author(s) Andrews, B.D. Inf. Syst. Lab., Stanford Univ., CA, USA Effros, M. ; Chou, P.A. ; Gray, R.M.Keywords
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