A model parameter and MAD prediction scheme for h.264 macroblock layer rate control

In this paper, we show that inaccurate model parameters degrade performance of R-Q model based rate control, and oscillations of estimated model parameters often occur in the classic quadratic R-Q model based macroblock (MB) layer rate control. To resolve the parameter oscillation problem, we thus propose to use a linear R-Q model rather than the quadratic R-Q model for MB layer rate control and a novel context-adaptive scheme for estimating mean absolute difference (MAD) and parameters for the linear R-Q model. The proposed context is adaptively computed according to local video signal characteristics using a Manhattan distance metric and an improved 2D sliding window method. Extensive experiments show that compared to the H.264 reference JM software, MB layer rate control algorithm using our proposed scheme significantly improves the MAD and model parameters prediction accuracy and bit achievement accuracy, and hence obtains much better rate distortion performance.