Rate distribution between model and signal for multiple descriptions

We consider the rate allocation problem for multiple-description quantization of the signal described by an adaptive model with a fixed structure. The source modeling in coding generally results in a two-stage description of the data, where one of the stages describes the model parameters, and the other describes the signal. Such a setup implies the existence of a trade-off between the rate spent on the parameters and the rate spent on the signal. We optimize this trade-off analytically for the multiple-description case using a method inspired by Minimum Description Length principle. We also provide an algorithm for optimizing the rate allocation between the components of the model-based multiple description coder. Finally we experimentally confirm our results. Our method facilitates the rate-adaptive multiple-description coding.