Artificial evolution for computer graphics
Proceedings of the 18th annual conference on Computer graphics and interactive techniques
Evolutionary Art and Computers
Evolutionary Art and Computers
Evolutionary Signal Enhancement Based on Hölder Regularity Analysis
Proceedings of the EvoWorkshops on Applications of Evolutionary Computing
On Generating HTML Style Sheets with an Interactive Genetic Algorithm Based on Gene Frequencies
AE '99 Selected Papers from the 4th European Conference on Artificial Evolution
GECCO '96 Proceedings of the 1st annual conference on Genetic and evolutionary computation
De-noising by soft-thresholding
IEEE Transactions on Information Theory
Case-Based facial action units recognition using interactive genetic algorithm
ACII'05 Proceedings of the First international conference on Affective Computing and Intelligent Interaction
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We present in this paper a multifractal bayesian denoising technique based on an interactive EA. The multifractal denoising algorithm that serves as a basis for this technique is adapted to complex images and signals, and depends on a set of parameters. As the tuning of these parameters is a difficult task, highly dependent on psychovisual and subjective factors, we propose to use an interactive EA to drive this process. Comparative denoising results are presented with automatic and interactive EA optimisation. The proposed technique yield efficient denoising in many cases, comparable to classical denoising techniques. The versatility of the interactive implementation is however a major advantage to handle difficult images like IR or medical images.