Fast hierarchical block matching algorithm utilizing spatial motion vector correlation

A new hierarchical block matching algorithm specially proper for a large search area, is proposed. The algorithm utilizes the spatial motion vector correlation under the fixed hierarchical search structure. Motion vectors of the causally neighboring blocks can be used to predict the motion vector of the current block, if the spatial motion vector correlation is strong. However, they are not helpful for searching complex or random motion. The proposed algorithm consists of two level searching steps. The higher one selects two initial estimates, one obtained by using motion vector correlation for continuous-motion, the other by using minimum mean absolute difference (MAD) for random or complex motion among rectangularly-sampled motion vector candidates in the search area, and the lower one is for the final motion vector refinement. Compared with previous hierarchical block matching algorithms, the scheme improves the accuracy of the estimated motion vector for random/complex motion as well as continuous motion. It is also proper for hardware implementation because of simple, fast, and regular search procedure. Simulation results show that the proposed algorithm drastically reduces the computational complexity to 5.0% of that of full search block matching algorithm, with the minor PSNR degradation of 0.4 dB even in the worst case.