An optimal fuzzy filter for Gaussian noise in color images using bacterial foraging algorithm

This paper presents an optimal fuzzy filter for Gaussian noise in color images using Bacterial Foraging Algorithm (BFA) and cosine similarity. The filter makes use of the relationship between different color components of a pixel to remove the noise from the color images. The adaptive cosine similarity between the central pixel and the neighboring pixels is estimated using color pairs red-green, red-blue and green-blue for noise removal. The membership function Large is defined and used to fuzzify similarity of each color component. Mean Square Error is used as an objective function for the bacterial foraging algorithm to learn the parameters of membership function Large. The correction term for the Gaussian filter is calculated using weighted average of the weights of all the neighboring pixels. The proposed Gaussian filter is found to be effective in eliminating noise from color images with the significant improvement in image quality. The experimental result on several color images proves the efficacy of the proposed fuzzy filter.