A unified approach for encoding clean and noisy sources by means of waveform and autoregressive model vector quantization

Data compression by vector quantization is considered for sources which have been degraded by noise. It is shown that, by appropriately modifying the given distortion measure, the problem becomes a standard quantization problem for the noisy source and the modified distortion measure. For the special case of sources corrupted by statistically independent additive noise, the authors provide sufficient conditions on the original distortion measure and probability distributions of the source and the noise for convergence of the generalized Lloyd algorithm in designing the quantizers. The results are specialized to waveform and autoregressive model vector quantization using the weighted quadratic and the Itakura-Saito distortion measures, respectively