An adaptive motion estimation algorithm based on evolution strategies

Based on evolution strategies (ESs), a novel adaptive motion estimation search algorithm (AESME) is presented. ESs consider evolutionary progress on the phenotype level. In contrast, genetic algorithms focus on heredity genetic mechanisms on the chromosome level. In ESs, the mutation operation accords with the normal distribution law. In the AESME algorithm, the (μ, λ)-ES algorithm is adopted to block motion estimation, and the adaptive scheme is advanced to improve the convergence rate on the basis of the 1/5 success rule. Experimental results demonstrate that this algorithm has similar performance to that of the full-search (FS) algorithm, and owing to the inherent parallelism and low complexity of ESs, AESME is suitable for VLSI implementation.