Bayesian motion estimation and interpolation in interlaced video sequences

Motion estimation in video is a very important tool for such applications as interpolation, motion compensation, and segmentation. However, in interlaced video, it is often desirable to perform interpolation prior to the motion estimation. In this correspondence, a novel technique is presented that, rather than minimizing the interpolation error in each of the frames used for motion estimation, seeks to make these errors equal. The new method is shown to perform deinterlacing better than several other approaches also based on Bayesian estimation.