Design of a highly effective multi-layered fuzzy logic based image enhancement filter

Abstract

This paper describes the development of an effective fuzzy image filter which consists of a multi-layered fuzzy structure 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.