Why B-pictures work: a theory of multi-hypothesis motion-compensated prediction

Abstract

This paper presents a theoretical analysis of multi-hypothesis motion-compensated prediction for hybrid video coders. The power spectrum of the prediction error is related to the displacement error PDFs of an arbitrary number of hypotheses in a closed form expression. It is shown that, if the residual noise level is low, doubling the number of (equally good) hypotheses can yield a gain of up to 0.5 bits/sample and that doubling the accuracy of motion compensation (such as going from integer-pel to 1/2-pel accuracy) can additionally reduce the bit-rate by up to 0.5 bits/sample independent of N. With realistic residual noise levels, the introduction of B-frames or overlapped block motion compensation typically provides larger gains than doubling the motion compensation accuracy.