Mean-Median Filtering for Impulsive Noise Removal

The objective of this paper is a new Mean- Median filtering for de-noising extremely corrupted images by impulsive noise. Whenever an image is converted from one form to another, some of degradation occurs at the output. Improvement in the quality of these degraded images can be achieved by the application of Restoration and /or Enhancement techniques. Noise removing is one of the categories of Enhancement. Removing noise from the original signal is still a challenging problem. Mean filtering fails to effectively remove heavy tailed noise & performance poorly in the presence of signal dependent noise. The successes of median filters are edge preservation and efficient attenuation of impulsive noise. An important shortcoming of the median filter is that the output is one of the samples in the input window. Based on this mixture distributions are proposed to effectively remove impulsive noise characteristics. Finally, the results of comparative analysis of mean-median algorithm with mean, median filters for impulsive noise removal show a high efficiency of this approach relatively to other ones