An adaptive reference frame selection method for multiple reference frame motion estimation in the H.264/AVC

The H.264/AVC achieves higher coding efficiency than the previous video coding standards such as MPEG-4 and H.263. H.264 adopted the multiple reference-frame motion estimation (MRF-ME). Although this new technique significantly improves the prediction accuracy, it requires very heavy encoding complexity in proportion to the number of reference frames. In this paper, we propose an adaptive reference-frame selection (ARFS) method using neighboring reference-frame information and Bayes theory. We show that the proposed algorithm effectively reduces the encoding complexity of MRF-ME and achieves similar coding gain, compared to the previous methods.