On spatial adaptation of motion-field smoothness in video coding

Abstract

Most motion-compensation methods dealt with in the literature make strong assumptions about the smoothness of the underlying motion field. For instance, block-matching algorithms assume a blockwise-constant motion field and are adequate for translational motion models; control-grid interpolation assumes a blockwise bilinear motion field and captures zooming and warping fairly well. Time-varying imagery, however often contains both types of motion (as well as others), and hence exhibits a high degree of spatial variability of its motion-field smoothness properties. We develop a simple method to spatially adapt the smoothness of the motion field. The proposed method demonstrates substantial improvements in video quality over a wide range of bit rates. To this end, we introduce the notion of a motion field that is characterized by a set of labels. The labels provide the flexibility to adaptively switch between two different motion models locally. The individual motion models have very different smoothness properties. The switched framework for motion compensation performs significantly better than each of its constituent motion models, in terms of both visual quality and signal-to-noise ratio (0.3-0.7 dB on the average). Finally, we develop an extension of this method that enhances the overlapped block motion compensation scheme by allowing spatial adaptation of the window function.