Design of a Pareto-optimization environment and its application to motion estimation

The characteristics of modern video signal processing algorithms are significantly influenced by a multitude of different configuration parameters. Hence, the selection of an optimum parameter set becomes a difficult task, since often various quality metrics have to be regarded, leading to a so-called multi-objective optimization problem. Furthermore, the high computational effort typically restricts the maximum possible number of simulated parameter configurations. Therefore, a flexible environment for multi-objective optimization of configuration parameters has been elaborated which uses evolutionary algorithms to efficiently explore the design-space. This environment is applied here for a detailed analysis and Pareto-optimization of a complex state-of-the-art motion estimation algorithm being used for frame rate conversion.