A new fuzzy filter for gaussian noise reduction

A new fuzzy filter is presented for the noise reduction of images corrupted with additive gaussian noise. The filter consists of two stages. The first stage computes a fuzzy gradient for eight different directions around the currently processed pixel. The second stage uses the fuzzy gradient to perform fuzzy smoothing by taking different contributions of neighbouring pixel values. The two stages are both based on fuzzy rules which make use of membership functions. The filter can be applied iteratively to effectively reduce heavy noise. The shape of the membership functions is adapted according to the remaining noise level after each iteration, making use of the distribution of the homogeneity in tile image. The fuzzy operators are implemented by the classical minimax. Experimental results are obtained to show the feasibility of the proposed approach. These results are also compared to other filters by numerical measures and visual inspection.