In view of the fact that the classical fast motion estimation methods are easy to fall into local optimum and suffer the high\r\ncomputational cost, the convergence of the motion estimation method based on the swarm intelligence algorithm is very slow.\r\nA new block motion estimation method based on single-dimension perturbation glowworm swarm optimization algorithm is\r\nproposed. Single-dimension perturbation is a local search strategywhich can improve the ability of local optimization.Theproposed\r\nmethod not only has overcome the defect of falling into local optimum easily by taking use of both the global search ability of\r\nglowwormswarmoptimization algorithm and the local optimization ability of single-dimension perturbation but also has reduced\r\nthe computation complexity by using motion vector predictor and terminating strategies in view of the characteristic of video\r\nimages. The experimental results show that the performance of the proposed method is better than that of other motion estimation\r\nmethods for most video sequences, specifically for those video sequences with violentmotion, and the searching precision has been\r\nimproved obviously. Although the computational complexity of the proposed method is slightly higher than that of the classical\r\nmethods, it is still far lower than that of full search method.
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