Transforms for Motion-Compensated Residuals Based on Prediction Inaccuracy Modeling
Xun Cai, Jae Sun Lim · 2016
In many video coding systems, motion compensation is used to reduce temporal correlation. Motion-compensated residuals are encoded with transforms. In this paper, we develop transforms for motion-compensated residuals based on prediction inaccuracy modeling. Specifically, we observe that motion-compensation is very effective in smooth regions and still regions. In regions where strong motions occur, the accuracy of motion-compensation is sensitive to the accuracy of motion vectors and local changes of image data. From this observation, we propose a model for the motion-compensated residuals. Based on this model, we relate the residual covariance function to the gradient function of the reference frame. The KLT of the covariance function is proposed. Experimental results show that a significantly smaller number of transform coefficients are needed in preserving the same amount of energy with the proposed transform.