Title :
Optimal variable-rate mean-gain-shape vector quantization for image coding
Author :
Lightstone, Michael ; Mitra, Sanjit K.
Author_Institution :
Chromatic Res. Inc., Sunnyvale, CA, USA
fDate :
12/1/1996 12:00:00 AM
Abstract :
A method for rate-distortion optimal variable rate mean-gain-shape vector quantization (MGSVQ) is presented with application to image compression. Conditions are derived within an entropy-constrained product code framework that result in an optimal bit allocation between mean, gain, and shape vectors at all rates. An extension to MGSVQ called hierarchical mean-gain-shape vector quantization (HMGSVQ) is similarly introduced. By considering the statistical dependence between adjacent means, this method is able to provide an improvement in the rate-distortion performance over traditional MGSVQ, especially at low bit rates. Simulation results are provided to demonstrate the rate-distortion performance of MGSVQ and HMGSVQ for image data
Keywords :
entropy codes; image coding; optimisation; rate distortion theory; statistical analysis; vector quantisation; HMGSVQ; MGSVQ; entropy constrained product code; gain vectors; hierarchical mean gain shape vector quantization; image compression; image data; low bit rates; mean gain shape vector quantization; mean vectors; optimal bit allocation; optimal variable rate; rate distortion performance; shape vectors; simulation results; statistical dependence; Bit rate; Cost function; Distortion measurement; Encoding; Image coding; Lagrangian functions; Product codes; Rate-distortion; Shape; Vector quantization;
Journal_Title :
Circuits and Systems for Video Technology, IEEE Transactions on
