On modelling the hybrid video coding for analysis and future development

Most of the work for the design and optimization of the hybrid video codecs is carried out experimentally. It is always desirable to have a proper theoretical treatment of the motion-compensated video coding system, which is extremely useful for making an analysis of the codecs available nowadays, and for designing new and efficient codecs for future applications. It requires many assumptions and simplifications. A simple Markov model with the assumption of wide-sense stationary signals may not work as well. To resolve the problem, we consider that prediction errors are the result of a motion estimation algorithm. A net deformation of pixels in a block along a certain direction is a more general situation. We make use of the first order Markov model to derive an approximated separable autocorrelation model for the block based motion compensation frame difference (MCFD) signal. Results of our experimental work show that the derived model can describe the statistical characteristics of the MCFD signals accurately. In the derivation of the initial model, we borrowed some concepts from the affine transform; however, our model is general and the theory behind is fundamental. It can be used as an analytical tool to study the effect of different sub-block sizes in the H.264 encoder, say for example. This enables us to enhance our understanding of mode selection and eventually facilitates the design of a new and efficient video encoder.