In most of multifocus image fusion methods

the parameter configuration of fusion model is usually based on experience.In this paper

a new multiobjective optimization method of multifocus image fusion based on IMOPSO (Improved Multiobjective Particle Swarm Optimization) is presented

which can simplify the model of multifocus image fusion and overcome the limitations of traditional methods.First the proper evaluation indices of multifocus image fusion are given

then the uniform model of multifocus image fusion in DWT (Discrete Wavelet Transform) domain is constructed

in which the model parameters are selected as the decision variables

and finally IMOPSO is designed to optimize the decision variables.IMOPSO not only uses a mutation operator to avoid earlier convergence

but also uses a crowding operator to improve the distribution of nondominated solutions along the Pareto front

and uses a new adaptive inertia weight to raise the optimization capacities.Experiment results demonstrate that IMOPSO has a higher convergence speed and better search capacities

and that the method of multifocus image fusion based on IMOPSO achieves the Pareto optimal image fusion.