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Two-Pass Bi-Directional Optical Flow Via Motion Vector Refinement

机译:运动矢量细化的双向双向光流

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Bi-directional optical flow (BDOF) is an efficient coding tool that has been recently adopted into Versatile Video Coding (VVC) standard. With BDOF, bi-predictive prediction samples of one coding block are enhanced via higher-precision motion vectors (MVs) derived from its two reference blocks. In this way, the energy of prediction error could be reduced, resulting in better coding performance. In VVC, the derived motion information is only used to enhance prediction samples. In this paper, it is proposed to use the derived motion information to also refine decoded MVs. The refined MVs may be used as spatial motion vector prediction (MVP) for the following coding units (CUs), as the temporal MVP for the subsequent pictures, and in the deblocking filtering process. Furthermore, the refined MVs can be used to perform motion compensation (MC) again to further improve the quality of the prediction samples. Simulation results show that the proposed methods can achieve -1.18% BD-rate saving in average under the random access configuration on top of the existing BDOF design in VVC.
机译:双向光流(BDOF)是一种有效的编码工具,最近已被多功能视频编码(VVC)标准所采用。使用BDOF,一个编码块的双向预测样本将通过从其两个参考块派生的更高精度的运动矢量(MV)得到增强。这样,可以减少预测误差的能量,从而获得更好的编码性能。在VVC中,导出的运动信息仅用于增强预测样本。在本文中,提出了使用导出的运动信息来细化解码的MV。精制的MV可以用作随后的编码单元(CU)的空间运动矢量预测(MVP),用作后续图片的时间MVP以及在去块滤波处理中。此外,精炼的MV可以再次用于执行运动补偿(MC),以进一步提高预测样本的质量。仿真结果表明,在VVC中现有BDOF设计的基础上,所提出的方法在随机访问配置下平均可节省-1.18%的BD速率。

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