Accurate parameter estimation and efficient fade detection for weighted prediction in H.264 video compression

Weighted prediction is a useful tool in video compression to encode scenes with lighting changes, such as fading scenes. Estimating weighted prediction parameters has been extensively discussed in the literature, however no mathematical model has been proposed. Moreover, the detection of the fading scenes in a real-time encoding system has received little attention. This paper addresses both of these aspects. An accurate parameter estimation algorithm for H.264 encoding is first derived for both the multiplicative factor and the additive offset based on a fading model. An efficient algorithm is then proposed to detect fade in a real-time encoding system, with simple statistics calculations, very low storage requirement, and low encoding delay. Simulation results show very accurate detection and compression gains of 5∓30% over existing techniques.