Improved Smoothing Filters Effects Using Mamdani Neuro Fuzzy Network PDF

Keywords

Impulsive noise, Median filter, Average filter, Mamdani neurofuzzy, Adaptive backpropagation algorithm.

Abstract

The results of the noise removal have a strong influence on the quality of the other image processing techniques. And since the main goal for any noise removal method is the preservation of the edges and image information, this influence is the principal drawback of the smoothing filters. In this paper, a modified Mamdani neurofuzzy network scheme has been proposed and presented to improve effects of smoothing filters in removing impulsive noise. The number of connections is reduced to be equal to the number of membership functions plus one. A training strategy for the presented neurofuzzy is based on artificial image which reduces the time of computation. The Analysis shows that the proposed neurofuzzy works well in suppressing impulsive at different noise ratios for grayscale and truecolor images.