New Nonlinear Filtering Strategies for Eliminating Medium and Long Tailed Noise in Images with Edge Preservation Properties

Abstract

Arithmetic filters are quite effective in recovering the images confounded by medium-tailed (Gaussian) noise. These filters, however, perform poorly in the presence of additive long-tailed (impulse) noise and they do not preserve edge structures. Median smoother discards outliers (impulses) effectively, but it fails to provide adequate smoothing for images corrupted with non-impulsive noise. In this paper, two new nonlinear techniques for image filtering, which we call New Filter I and New Filter II, are proposed based on a recently developed nonlinear highpass filter algorithm. New Filter I suppresses Gaussian noise quite well. New Filter II effectively eliminates impulses and filters out noise having Gaussian statistics. Both the Alters are shown to have good edge preserving characteristics. The proposed filters are evaluated for their performance on a test image and the results obtained are included.