A novel noise-free pixels based Impulse noise filtering

Abstract

Generally, impulse noise filtering schemes consider all pixels within a large neighborhood. However, the estimate from all pixels within the neighborhood may not be accurate. Moreover, large window may remove edges and fine details. In contrast to this approach, we propose iterative impulse noise removal scheme that emphasizes on few noise-free pixels within a small neighborhood. This iterative process continues until all noisy pixels are replaced with the estimated values. To estimate the optimal value of noisy pixel, we developed genetic programming (GP) based estimator using noise-free pixels. The estimator is constituent of useful local pixels information. Experimental results show that the proposed scheme is capable of removing impulse noise effectively while preserving the fine details. Especially, our approach has shown effectiveness against high impulse noise density.