NEURAL FILTERING TECHNIQUE FOR ENHANCING DIGITAL IMAGES
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A new image enhancement technique proposed in this paper. The proposed neural filter is carried out in two stages. In first stage the corrupted image is filtered by applying a special class of multistate switching median filter. The filtered image output multistate switching median filter is 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. 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 conventional filters and neural filters.