A Novel Framework for Enhancing Images Corrupted by Impulse Noise Using Type-II Fuzzy Sets

This paper presents a novel type-II fuzzy filter to remove impulse noise in an image. The filter processes impulses as type-II fuzzy sets. Type-II fuzzy sets model uncertainties more effectively than type-I fuzzy sets because the membership function for a type-I fuzzy set for a particular input is a crisp value. The proposed algorithm firstly detects impulses by considering grayscale distribution amongst neighbouring pixels and then determines the presence of impulsive pixels by comparing it with a range of threshold values using an S - shaped fuzzy membership function that is itself fuzzy. As the level of contamination varies from pixel to pixel, the modified value for the noisy pixel is calculated depending on the impulse noise present in it. The better performance of the filter is demonstrated on the basis of PSNR values calculated from the original and restored images respectively.