Adaptive non linear filtering with improved performance for removal of high density impulse noise in images

Abstract

Impulse noise is a special type of noise which can have many different origins Images are often corrupted by impulse noise caused by transmission errors faulty memory locations or timing errors in analog to digital conversion The impulse noise can be broadly classified into salt and pepper noise and random valued impulse noise The salt and pepper noise can corrupt the image where the noisy pixels can take only the maximum and minimum gray values in the dynamic range But the random valued impulse noise can take any value between the maximum and minimum gray values in the dynamic range Since linear filtering techniques are not effective in removing impulse noise non linear filtering techniques are widely used in the restoration process Median filters are well known for their capability to remove impulse noise as well as preserve edges The main drawback of a Standard Median Filter is that it is effective only for low noise densities At high noise densities SMFs often exhibit blurring for large window sizes and insufficient noise suppression for small window sizes When the noise density is over 50 percent the edge details of the original image will not be preserved by the median filter However most of the median filters operate uniformly across the image and thus tend to modify both noise and noise free pixels Consequently the effective removal of impulse noise often leads to images with blurred and distorted features Ideally the filtering should be applied only to corrupted pixels while leaving uncorrupted pixels intact newline