Four-step genetic search for block motion estimation
M.F. So, A. Wu · 2002
Genetic algorithms (GA) are well known for searching global maxima and minima. In general, number of search points required by GA for searching global extreme is much lower than the exhausted search. GA have been applied to the block matching algorithm (BMA) and demonstrate positively its capability in the BMA. The mean square error (MSE) performance of GA based BMA is close to full-search (FS). However, the disadvantage of GA is the computational requirement for practical use. A four-step genetic search algorithm is proposed for the BMA. The proposed method takes advantage of GA and 4SS. The simulation result shows the proposed method has a similar performance to full-search (FS) in terms of the MSE. In addition, the number of search points required by the proposed algorithm is approximately equal to 14% of the FS and is close to three-step search (3SS). The speed up ratio between the proposed algorithm and FS is 5.6 times.