An analytical framework for overlapped motion compensation

Motion compensated interframe prediction is a key technology used to accomplish efficient video codecs. This paper presents a novel framework which proves the superiority of overlapped motion compensation. The window design problem is revised by introducing a statistical model of the motion estimation process. The result clarifies the relationship between the optimum window and image characteristics in an explicit formula and quantifies the prediction error reduction achieved by overlapped motion compensation. Experimental results using real image sequences support the proposed theory and demonstrate its superiority. Overlapping in warping prediction is also considered and its effectiveness is shown.