Design of an hierarchical fuzzy filter for removal of heavy impulse noise from corrupted images

In this paper we discuss the design of a digital image enhancement system based on a Hierarchical Fuzzy Logic (HFL) approach. Hierarchical fuzzy systems, first introduced in[10], are capable of substantially reducing the number of fuzzy rules to be learnt. We show how Evolutionary Algorithms (EAs) can be used to learn the fuzzy rules in a fuzzy image filter as opposed to determining the rules using human intuition. Results are presented for the well-known 'Lena' image and another 'Hill' image to prove that the newly designed hierarchical filter had acquired sufficient knowledge to enhance images which were not used during the training phase of the algorithm.