On the motion compensated prediction error using true motion fields

For hybrid video coding, knowledge about the prediction error statistics is needed for both, application of source coding theory and efficient motion estimation. A statistical model for the joint probability density function (pdf) of the prediction error signal in a hybrid coding environment is proposed. The model claims segmentwise stationarity of the prediction error. It is based on spherically invariant random processes (SIRPs) and allows modeling of correlations inside the segments as well as varying univariate distributions for the different segments. Computer experiments show a good fit of the proposed model to actual statistics of prediction error signals which were obtained by motion compensation under idealized conditions