A MULTI-SCALE TWO-STEP FAST SEARCH ALGORITHM FOR BLOCK MOTION ESTIMATION

Block motion estimation using full search is computationally intensive. Previously proposed fast algorithms reduce computation by limiting the number of search locations and search directions in a predefined search region. This is accomplished at the expense of accuracy of motion estimation and a large mean squared error for motion-compensated images, especially for image sequences with large displacement and rotation. In this paper, a novel efficient search algorithm for block motion estimation is presented to produce better performance than some fast search algorithms that have been developed, such as three step search, orthogonal search, 2D-logarithmic search, four step search, and block-based gradient descent search, in large displacement and rotation image cases. The proposed algorithm is based on the notion of locally multi-scale operation, search of global minimum, and two layer search strategy. Experimental results show that the proposed algorithm produces anticipative performance while costing much less computation power than the full search algorithm.