Design of Optimizing Stack Filters by an Ant Colony - Clonal Selection Algorithm

Stack filters are a class of nonlinear digital filters that satisfy a weak superposition property known as the threshold decomposition and stacking property. They have good performances of suppressing noises and preserving details. Their design is formulated as a course of optimizing PBF. This paper presents an ant colony-clonal selection algorithm for stack filters´ optimizing. Under the MMAE criterion, the capability of the stack filters optimized by this method has been proven through simulation. And the results prove its advancing compared with the stack filters optimized by genetic algorithm, particle swarm algorithm and clonal selection algorithm.