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Evolutionary Design of Local Image FIlters
Gall, Samuel ; Hurta, Martin (oponent) ; Sekanina, Lukáš (vedoucí práce)
This thesis focuses on the research and implementation of evolutionary design of local image filters. The aim is to create a tool capable of automatically designing suitable image operators for image filtering, specifically noise removal, using an evolutionary design method called Cartesian Genetic Programming (CGP). The tool was used for various experiments with different settings of CGP parameters such as grid size, population size, and mutation parameter. The created filters were compared with conventional noise removal filters. Evolved filters were tested on a set of test images, where their behavior was comparable to that of a median filter. Unlike the median filter, evolved filters were able to preserve more image quality.

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