Fuzzy filters design on image processing by genetic algorithm approach
Hung‐Ching Lu, Shian-Tang Tzeng · 2005
In this paper, we present a new nonlinear fuzzy filter for image processing in a mixed noise environment, where both additive Gaussian noise and non-additive impulsive noise may be present. In the past researches, it is not easy to combine these filters to remove mixed noise in an image processing environment without blurring the image details or edges. Trying to distinguish between noise and edge information in the image is an inherently ambiguous problem and naturally leads to the development of a fuzzy filter. We make use of local statistics to retain the membership function of a fuzzy filter with crossover, mutation, and selection operations for image processing to remove both Gaussian noise and impulsive noise while preserving edges.