[Show abstract][Hide abstract] ABSTRACT: In image processing, the rank filters are used to yield better noise removal ability for salt & pepper type noise. But they won’t
reproduce the images exactly for high noise density conditions. During image processing, varying noise density surely affects the de-noising
performance of the processing system. So, The Noise removal ability of system should be improved. Proper rank filter selection would be
important for this. Otherwise we may lose our precise information. In this work, three rank filter algorithms are compared to estimate their
performance in high noise density. We can infer the filters response from the results shown. Better Filtering selection can be achieved using
PSNR values presented from original and de-noised images.