Novel Adaptive Filter (NAF) for Impulse Noise Suppression from Digital Images

In general, it is known that an adaptive filter adjusts its parameters iteratively such as size of the workingwindow, decision threshold values used in two stage detection-estimation based switching filters, number ofiterations etc. It is also known that nonlinear filters such as median filters and its several variants arepopularly known for their ability in dealing with the unknown circumstances. In this paper an efficient andsimple adaptive nonlinear filtering scheme is presented to eliminate the impulse noise from the digitalimages with an impulsive noise detection and reduction scheme based on adaptive nonlinear filtertechniques. The proposed scheme employs image statistics based dynamically varying working windowand an adaptive threshold for noise detection with a Noise Exclusive Median (NEM) based restoration.The intensity value of the Noise Exclusive Median (NEM) is derived from the processed pixels in localneighborhood of a dynamically adaptive window. In the proposed scheme use of an adaptive thresholdvalue derived from the noisy image statistics returns more precise results for the noisy pixel detection. Theproposed scheme is simple and can be implemented as either a single pass or a multi-pass with a maximumof three iterations with a simple stopping criterion. The goodness of the proposed scheme is evaluatedwith respect to the qualitative and quantitative measures obtained by MATLAB simulations withstandard images added with impulsive noise of varying densities. From the comparative analysis it isevident that the proposed scheme out performs the state-of-art schemes, preferably in cases of high-densityimpulse noise.