An Adaptive Frame Interpolation Algorithm Using Statistic Analysis of Motions and Residual Energy

In this paper, a new motion-compensated frame interpolation (MCFI) algorithm using adaptive criterions to correct the motion vector field is proposed. First, an effective pre-processing scheme is done to the transmitted motion vectors. Then, unlike the conventional MCFI algorithms using fixed criterion to analyse the reliability of motion vectors, we proposed to select the parameters and thresholds by analysing the statistical characterization of motion vectors and residual energy, thus thresholds can be changed adaptively during the decoding process. Meanwhile, our new criterions consider both reliability of motion vectors and the smoothness of the region, which avoid the unnecessary motion estimation and reduce the complexity. Experimental results show that the proposed algorithm has 1.4 similar to 5.5 dB increase comparing with vector median filter algorithm in average PSNR, and greatly improves the subjective visual quality.