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Bayesian motion estimation and interpolation in interlaced video sequences

机译:隔行视频序列中的贝叶斯运动估计和插值

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摘要

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.
机译:视频中的运动估计对于插值,运动补偿和分段等应用是非常重要的工具。然而,在隔行视频中,通常期望在运动估计之前执行内插。在这种对应关系中,提出了一种新颖的技术,而不是最小化用于运动估计的每个帧中的内插误差,而是试图使这些误差相等。与基于贝叶斯估计的其他几种方法相比,该新方法显示出更好的去隔行性能。

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