Performance of Entropy-Constrained Block Transform Quantizers.
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An analysis of the rate-distorted performance of an entropy- constrained block transform quantization scheme operating on discrete-time stationary autoregressive process is presented. Uniform-threshold quantization is employed to quantize the transform coefficients. An algorithm for optimum stepsize (or, equivalently, entropy) assignment among the quantizers is developed. A simple asymptotic formula indicating the high rate performance of the block transform quantization schemes is presented. Finally, specific results determining the rate- distortion performance of the entropy-constrained block transform quantization scheme operating upon first-order Gauss-Markov and Laplace-Markov sources are presented and appropriate comparisons with the Haung and Schulthesis block transform quantization, vector quantization and predictive encoding are rendered.