Fast motion vector estimation for video coding based on multiresolution-spatiotemporal correlations

In this paper, we propose a new fast algorithm for motion vector (MV) estimation based on correlations of MVs existing in spatially and temporally adjacent as well as hierarchically related blocks. The main idea is to select a good set of MV candidates with information obtained at the coarser resolution level and spatio-temporal blocks at the same level, and then perform further local search to refine the MV result. The experimental results show that the proposed fast algorithm achieves a speed-up factor ranging from 150 to 310 with only 2 - 7% MSE increase in comparison with the full search block matching algorithm on typical test video sequences.