A new multi-layered fuzzy image filter for removing impulse noise

In this paper we develop a fuzzy image filter which consists of a multi-layered fuzzy structure based on the weighted fuzzy blend filter for the removal of noise from images heavily corrupted by impulse noise, while preserving the intricate details of the image. The introduction of multi-layered fuzzy systems substantially decreases the number of rules to be learnt. We then show how Evolutionary Algorithms (EAs) can be used to effectively learn the fuzzy rules in each knowledge base. Results are presented for impulse noise corruption of the well-known ‘Lena’ image.