The effect of input limiting on linear and nonlinear filters for the removal of impulsive noise

This paper investigates the effects of input limiting on the performance of linear and nonlinear filters when the input signal is contaminated by impulsive noise modeled as an alpha-stable (α-stable) random process. The nonlinear filters chosen are from the median family filters: median and recursive median filter, and Wiener filter from the linear filter group. The hypothesis being tested in this paper is that front-end limiting will increased the performance of median filter when the noise was extremely impulsive. Each image has been analyzed for four impulsive noise parameter values, α = 2, 1.5, 1, and 0.5 which cover a range of noise behaviors from Gaussian, through Cauchy, to impulsive. One method of handling very large impulses is to incorporate in the receiver over-voltage protection in the form of an analog limiter which clips the received signal before the filtering process. The simulation results obtained suggest that the front-end limiting enhances the performance of median filters in dealing with images, where it eliminates the highly impulsive noise while preserving useful detail in the image.