The fitness map scheme: application to interactive multifractal image denoising

AbstractInteractive 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 sufficient 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 difficult 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.

• Type: Conference
• Year: 2005
• Where: CEC
• Authors: Evelyne Lutton, Mario Pilz, Jacques Lévy Véhel
• Keywords: AbstractInteractive Evolutionary Algorithms, Artificial Intelligence, CEC 2005, Image Denoising Application, Multifractal Denoising Method