A new prediction model search algorithm for fast block motion estimation

Most of the fast block matching algorithms (BMAs) use the origin as the initial center of the search. To improve the accuracy of the fast BMAs, a new prediction model (PM) search algorithm is proposed. Based on the spatial correlation of motion and the fast center-biased BMA, the four causal neighbour blocks are chosen to predict the starting search point and then the center-biased BMA is used to find the final motion vector as the global minimum is closer to the predicted center. Experimental results show that the proposed prediction model improves the performance of most fast BMAs such as the new three-step search and the four-step search, in terms of the motion compensation errors. In addition, the average computational requirement is also reduced.