Image restoration based on GA-MCMC particle filters

Particle filter is applied in image restoration, in order to remove degeneracy phenomenon and alleviate the sample impoverishment problem. The global optimization and particle diversity of generic algorithm(GA) are introduced, and the convergence of Markov chain Monte Carlo (MCMC) method was combined, the crossover, mutation and selection operation were used in image restoration by particle filter, to enhance the robustness, accuracy and flexibility of the particle filter. Furthermore, a new image restoration algorithm by GA-MCMC particle filter is proposed. Simulation results showed that this method can reduce the impoverishment and degeneracy problems, and from the restoration results to mixed noisy image, we can see the effectiveness and superiority of the proposed algorithm.