Unbiased Variable Windows Size Impulse Noise Filter using Genetic Algorithm

Abstract

This paper proposes an Unbiased Variable Windows Size Impulse noise filter (UVWS) using a genetic algorithm to effectively restore the corrupted images with high or slight noise densities. The method consists of three stages. First, all pixels are classified into noisy and noise-free categories based on their intensities. In the second stage, the noisy pixels are pushed into a descending priority list the priority associated with each pixel is the number of noise-free pixels in the neighbor’s local window. Finally, for each pixel in the list, a local weighted average is calculated so that the corresponding weight for each neighbor is optimized by the genetic algorithm (GA). The performance of the proposed method is evaluated on several benchmark images and compared with four methods from the literature. The results show that the proposed method performs better in terms of visual quality and PSNR especially when the noise density is very high.