High-resolution quantization theory and the vector quantizer advantage

The authors consider how much performance advantage a fixed-dimensional vector quantizer can gain over a scalar quantizer. They collect several results from high-resolution or asymptotic (in rate) quantization theory and use them to identify source and system characteristics that contribute to the vector quantizer advantage. One well-known advantage is due to improvement in the space-filling properties of polytopes as the dimension increases. Others depend on the source´s memory and marginal density shape. The advantages are used to gain insight into product, transform, lattice, predictive, pyramid, and universal quantizers. Although numerical prediction consistently overestimated gains in low rate (1 bit/sample) experiments, the theoretical insights may be useful even at these rates