Hybrid neuro-fuzzy filter for impulse noise removal

摘要

A new filter is presented for images which are highly corrupted by impulse noise. The proposed operator is based on a hybrid neuro-fuzzy approach. The network structure of the filter is specifically designed to detect different patterns of noisy pixels typically occurring in highly corrupted data. The fuzzy mechanism embedded in the network aims at removing noise pulses without destroying fine details and textures. A learning method based on the genetic algorithms is adopted to adjust the network parameters from a set of training data. Experimental results show that the neuro-fuzzy filter is able to yield a very effective noise cancellation and to perform significantly better than state-of-the-art operators in the literature.