A New Decision-Based Adaptive Filter for Removal of High Density Impulse Noise from Digital Images

Abstract

High density impulse noise suppression using simple median filters results worst where these execute better to suppress the lower density impulse noise of corrupted images. Some advanced adaptive median and fuzzy based filters are able to remove the high density impulse noise but the image details are changed a little bit and also execution time is greater. In this paper, we proposed an efficient approach for suppression of impulse noise from digital images corrupted by up to 99% impulse noise using decision based adaptive filtering method as well as preserve the details of image. The method works in two different stages - noise detection using switching technique and finally noise suppression and restoration. Experimental results show that our method perform better in terms of PSNR bellow 80% noise density but above 80% noise density it is almost comparable with the latest methods.