The Fitness Map Scheme. Application to interactive multifractal image denoising
Résumé
Interactive evolutionary algorithms (IEA) often suffer from what is called the user bottleneck. In this paper, we propose and analyse a method to limit the user interactions, while still providing suficient informations for the EA to converge. The method has been currently developed on a multifractal image denoising application: a multifractal denoising method is adapted to complex images, but depends on a set of parameters that are quite dificult to tune by hand. A simple IEA has been developed for this purpose in a previous work. We now experiment an approximation of the user judgment, via a fitness map, that helps to reduce the number of user-interactions. The method is easily extensible to other interactive, or computationally expensive, evolutionary schemes.
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