Frame Rate Up Conversion Via Bayesian Motion Estimation

In this paper, a novel block-based motion compensated frame interpolation (MCI) algorithm is proposed to enhance the temporal resolution of video sequences. We formulated motion estimation into MAP framework, and solved it via Bayesian belief propagation. By effectively incorporating a priori knowledge of the motion field and optimizing the whole motion field synchronously, it could derive more accurate motion vectors than traditional methods. Finally, adaptive overlapped block motion compensation (OBMC) is used to reduce blocking artifacts. Experimental results show that the proposed method outperforms other methods in both objective and subjective quality.