Zhang Kai, Chen Yi-Wen, Zhanga Li, Chien Wei-Jung, Karczewicz Marta
IEEE Trans Image Process. 2018 Oct 22. doi: 10.1109/TIP.2018.2877355.
Affine Motion Compensation (AMC) is a promising coding tool in Joint Exploration Model (JEM) developed by the Joint Video Exploration Team (JVET). AMC in JEM employs a 4-parameter affine model between the current block and its reference block. With this model, Motion Vectors (MV) of each sub-block can be derived from the MVs at two control points. In this paper, we present a practical framework to further improve the AMC in JEM. First, we introduce a multi-model AMC approach, which allows the encoder to select either the 4-parameter affine model or the 6-paramter affine model adaptively. Second, we improve the affine inter-mode in two aspects. For the normative part, we present an efficient affine motion coding method, which replaces the affine MV Prediction (MVP) candidates in JEM with more accurate but simpler ones, and employs a second-order MVP. For the non-normative part, we enhance the motion estimation process for AMC, by regulating the optimization algorithm. Finally, we propose to unify the affine merge-mode and the normal merge-mode into a unified merge-mode, which combine affine merge candidates and normal merge candidates in a single merge candidate list. Partial of these methods have been adopted into the next generation video coding standard named Versatile Video Coding (VVC). Simulation results show that the proposed methods can achieve 1.67% BD rate savings in average for the random access configurations.
仿射运动补偿(AMC)是联合视频探索团队(JVET)开发的联合探索模型(JEM)中一种很有前景的编码工具。JEM中的AMC在当前块与其参考块之间采用四参数仿射模型。利用该模型,每个子块的运动矢量(MV)可从两个控制点的MV导出。在本文中,我们提出了一个实用框架来进一步改进JEM中的AMC。首先,我们引入了一种多模型AMC方法,该方法允许编码器自适应地选择四参数仿射模型或六参数仿射模型。其次,我们从两个方面改进仿射帧间模式。对于规范部分,我们提出了一种高效的仿射运动编码方法,该方法用更准确但更简单的候选仿射运动矢量预测(MVP)替换JEM中的候选仿射运动矢量预测,并采用二阶MVP。对于非规范部分,我们通过调整优化算法来增强AMC的运动估计过程。最后,我们建议将仿射合并模式和普通合并模式统一为一个统一的合并模式,该模式在单个合并候选列表中组合仿射合并候选和普通合并候选。这些方法中的一部分已被纳入名为通用视频编码(VVC)的下一代视频编码标准。仿真结果表明,所提方法在随机访问配置下平均可节省1.67%的BD率。