A novel flatted hexagon search pattern for fast block motion estimation
Thou-Ho Chen, Yifan Li · 2005
A speed-quality effective block-matching algorithm (BMA) based on the flatted-hexagon search (FHS) pattern is developed for motion estimation. The basic idea behind the proposed algorithm is that the covering range of a search pattern should be enlarged as horizontal as possible to find the optimal motion vector quickly due to the fact that the probability of horizontal-biased motions is larger than that of vertical-biased motions in most real-world image sequences. This reveals that both the searching-speed and matching-probability can be improved if the shape of a search pattern is flatted horizontally. Experimental results show that the proposed FHS is superior to other famous BMAs, such as the three-step search (3SS), diamond search (DS) and hexagonal-based search (HEXBS), in terms of speed-probability product improvement rate corresponding to the full search (FS).