An Artificial Intelligent Technique for Image Enhancement

A class of neural filter for image enhancement is proposed in this paper. The proposed intelligent filter is carried out in two stages. In first stage the corrupted image is filtered by applying two special classes of decision based filters. Filtered image outputs from decision based filters are suitably combined with a Feed forward neural network in the second stage. The internal parameters of the feed forward neural network are adaptively optimized by training for three well known images. This is quite effective in eliminating impulse noise. Extensive simulation results show that the proposed filter is superior in terms of eliminating impulse noise as well as preserving edges and the results are compared with other existing filters.