A Novel Fuzzy Filter for Impulse Noise Removal

Abstract

In this paper, we propose a novel Neural Fuzzy Filter (NFF) to remove impulse noise from highly corrupted images. The proposed filter consists of a fuzzy number construction process, a neural fuzzy filtering process and an image knowledge base. First, the fuzzy number construction process will receive sample images or the noise-free image, then construct an image knowledge base for the neural fuzzy filtering process. Second, the neural fuzzy filtering process contains of a neural fuzzy mechanism, a fuzzy mean process, and a fuzzy decision process to perform the task of impulse noise removing. By the experimental results, NFF achieves better performance than the state-of-the-art filters based on the criteria of Mean-Square-Error (MSE). On the subjective evaluation of those filtered images, NFF also results in a higher quality of global restoration.