Biogeography-based optimisation search algorithm for block matching motion estimation

Global optimisation methods such as genetic algorithm and particle swarm optimisation have been applied to motion estimation to prevent from being trapped into local minimum. However, their computational complexity is very high. To overcome this problem, a novel search algorithm for block motion estimation based on biogeography-based optimisation (BMEBBO) is proposed in this study. Since biogeography-based optimisation (BBO) has few initial parameters, fast convergence speed and high searching precision, BMEBBO can search global minimum effectively through the migration and the mutation operation of BBO. In addition, BMEBBO with chaotic search (BBOCHAO) is proposed to improve the local search ability of BMEBBO and a multi-mode algorithm combining BBOCHAO with diamond search (BBOCDS) is also proposed to improve the speed of BBOCHAO. Experimental results show that BBOCHAO has high prediction quality and low fluctuations of video quality especially for violent motion. BBOCDS can remarkably decrease the computational complexity of BBOCHAO with little sacrifice of peak signal-to-noise ratio. Moreover, BBOCDS is faster than test zero search algorithm in scalable video coding implementation with little sacrifice in rate–distortion sense.