Reduction in impulse noise in digital images through a new adaptive artificial neural network model

Abstract

In this paper, an adaptive artificial neural network model is developed in order to restore severely corrupted images. The proposed new and effective impulse noise reduction filter is named as adaptive neural network models with an algorithm based on artificial neural networks. Networks trained at different noise intensities get activated according to the intensity of the noise and estimate the most suitable neighboring pixel that can replace the corrupted pixel. The proposed algorithm reduces impulse noise effectively while also protecting the details. Experimental results show that the proposed algorithm performs better compared with other traditional filters.