Modeling of subband image data for buffer control

We develop an adaptive scheme for quantization of subband or transform coded frames in a typical video sequence coder. Using a generalized Gaussian model for the subband or transform coefficients, we present a procedure to determine the optimum dead-zone quantizer for a given entropy of the quantizer output symbols. We find that, at low bit rates, the dead-zone quantizer offers better performance than the uniform quantizer. The model is used to develop an adaptive procedure to update the quantizer parameters on the basis of the state of a channel buffer with constant output rate and variable input rate. We compare the accuracy of the generalized Gaussian model in predicting the actual bit rate to that achievable using the simpler and more common Laplacian model. Experimental results show that the generalized Gaussian model has superior performance than the Laplacian model, and that it can be effectively used in a practical scheme for buffer control.