| Hi-index | 0.43 |
Many modified three-step search (TSS) algorithms have been studied for the speed up of computation and improved error performance over the original TSS algorithm. In this work, an efficient and fast TSS algorithm is proposed, which is based on the unimodal error search assumption (UESA), error surface properties, the matching error threshold and the partial sum of the matching error. For the search strategy, we propose a new and efficient search method, which shows a good performance in terms of the computational reduction and the prediction error compared with other search algorithms. Also, we add half-stop algorithms to the above algorithm with little degradation of the predicted image quality while obtaining more computational reduction. One of them is based on the assumption that if a small amount of motion compensation error is produced, we can consider the matching block as a matched block and the motion vector as a global one. The other removes the computational redundancy by stopping the useless calculation of the matching error in a matching block. With the added algorithms, we can reduce significantly the computation for the motion vector with a small degradation of the predicted image quality with a proper threshold. Experimentally, it is shown that the proposed algorithm is very efficient in terms of the speed up of the computation and error performance compared with other conventional modified TSS algorithms