Block-Matching Translational and Rotational Motion Compensated Prediction Using Interpolated Reference Frame

Motion compensated prediction (MCP) implemented in most video coding schemes is based on translational motion model. However, nontranslational motions, for example, rotational motions, are common in videos. Higher-order motion model researches try to enhance the prediction accuracy of MCP by modeling those nontranslational motions. However, they require affine parameter estimation, and most of them have very high computational complexity. In this paper, a translational and rotational MCP method using special subsampling in the interpolated frame is proposed. This method is simple to implement and has low computational complexity. Experimental results show that many blocks can be better predicted by the proposed method, and therefore a higher prediction quality can be achieved with acceptable overheads. We believe this approach opens a new direction in MCP research.