This article investigates the use of genetic algorithms in image denoising by non-linear (ordering-based) filters. It proposes a computational effective method for the genetic-based filter synthesis, that uses a model-free approach (no assumptions being made on the noise distribution or the image contents). The main originality is that the proposed method uses artificially (synthesised) test images for the noise estimation and filter design.
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