Fast block motion estimation algorithm based on motion classification and directional search patterns

Abstract

This paper suggests a simple scheme of block motion estimation in which the search pattern is divided into a number of sectors. By employing prediction the motion vector search is constrained to a small area. In the first step five neighboring blocks are searched for finding the predicted motion vector. The vector thus obtained is chosen as the initial search center. This predictive search center is closer to the global minimum and thus decreases the effect of the monotonic error surface assumption on the motion field estimates. Secondly, the prediction information is used to obtain the direction of the predicted motion vector. Based on that direction, the search area is divided into eight sectors. Thirdly, the magnitude of the predicted motion vector is used to define the motion content of different blocks. Thus the final search pattern dynamically uses the motion magnitude and motion direction information and significantly reduces the computational complexity. Experimental results show speed improvement of the proposed algorithm over other fast search algorithms; in addition, the image quality measured in terms of peak SNR also shows good results.