Fast mode selection scheme for H.264/AVC inter prediction based on statistical learning method

H.264 adopts variable block size motion estimation and rate-distortion-optimization based mode decision to improve video quality and compression ratio. These techniques have made H.264 better than other existing video coding standards. However, they are computationally intensive and time-consuming. In this paper, a fast mode selection scheme is proposed for H.264 inter prediction. Firstly, the first few frames are encoded and thresholds are acquired through a statistical learning process. Then, for the rest of frames, motion estimation and mode decision are only performed for the candidate modes which are selected with the proposed fast mode selection scheme. The proposed approach is applicable to all existing motion search algorithms. Besides, thresholds are on-line computed separately for each sequence. Results show that the total encoding time is saved by 57.2% on average with negligible video quality degradation.