Design and Development of an Improved Adaptive Median Filtering Method for Impulse Noise Detection

Abstract

An Impulse noise detection and removal with adaptive filtering approach is proposed to restore images corrupted by salt & pepper noise. The proposed algorithm works well for suppressing impulse noise with noise density from 5 to 60% while preserving image details. The difference of current central pixel with median of local neighborhood pixels is used to classify the central pixel as noisy or noise-free. The noise is attenuated by estimating the values of the noisy pixels with a switching based median filter applied exclusively to those neighborhood pixels not labeled as noisy. The size of filtering window is adaptive in nature, and it depends on the number of noise-free pixels in current filtering window. Simulation results indicate that this filter is better able to preserve 2-D edge structures of the image and delivers better performance with less computational complexity as compared to other denoising algorithms existing in literature.