Title :
Necessary conditions for the optimality of variable-rate residual vector quantizers
Author :
Kossentini, Faouzi ; Smith, Mark J T ; Barnes, Christopher F.
Author_Institution :
Digital Signal Process. Lab., Georgia Inst. of Technol., Atlanta, GA, USA
fDate :
11/1/1995 12:00:00 AM
Abstract :
Necessary conditions for the optimality of variable-rate residual vector quantizers are derived, and an iterative descent algorithm based on a Lagrangian formulation is introduced for designing residual vector quantizers having minimum average distortion subject to an entropy constraint. Simulation results for entropy-constrained residual vector quantizers are presented for memoryless Gaussian, Laplacian, and uniform sources. A Gauss-Markov source is also considered. The rate-distortion performance is shown to be competitive with that of entropy-constrained vector quantization and entropy-constrained trellis-coded quantization
Keywords :
Gaussian processes; Markov processes; entropy; iterative methods; optimisation; rate distortion theory; source coding; vector quantisation; Gauss-Markov source; Lagrangian formulation; Laplacian sources; entropy constraint; iterative descent algorithm; memoryless Gaussian sources; minimum average distortion; necessary conditions; optimality; rate-distortion performance; simulation; source coding; uniform sources; variable-rate residual vector quantizers; Algorithm design and analysis; Design methodology; Entropy; Gaussian processes; Iterative algorithms; Lagrangian functions; Laplace equations; Signal processing algorithms; Source coding; Vector quantization;
Journal_Title :
Information Theory, IEEE Transactions on
