Subband coding systems incorporating quantizer models

Abstract

A new method for dealing with the effects of quantization in a subband system is proposed. It uses the "gain plus additive noise" linear model for the Lloyd-Max quantizer. Based on this, it is demonstrated how, by an appropriate choice of synthesis filters, one can cancel all signal-dependent errors at the output of the system. The only remaining error is random in nature and not correlated with the input signal. We therefore have a tradeoff between the error being only random or having signal-dependent components as well (since the error variances in both cases are comparable). As a result of having only a random error, it is possible to reduce this error using, for example, a noise removal technique. The result is then extended to the case where the input is a multidimensional signal, and arbitrary sampling lattices are used, as well as to the QMF (alias cancellation) case. To demonstrate the validity of the proposed approach, two types of experiments on images are carried out: In a toy example, it is shown that using noise removal could be beneficial. For a more realistic coding scheme, however, it is demonstrated that even in the case when the model is no longer valid (when some of the subbands are discarded), the output error is still much less correlated with the input signal as opposed to the commonly used subband system, while visually, the reconstructed images look very similar.