Abstract
Most approaches to multi-resolution image fusion are based on experience, and the fusion results are not the optimal. In this paper, a new approach to multi-resolution image fusion based on AMOPSO-II (Adaptive Multi-Objective Particle Swarm Optimization) is presented, which can achieve the optimal fusion results through optimizing the fusion parameters. First the uniform model of multi-resolution image fusion in DWT (Discrete Wavelet Transform) domain is established; then the proper evaluation indices of multiresolution image fusion are given; and finally AMOPSO-II is proposed and used to search the fusion parameters. AMOPSO-II not only uses an adaptive mutation operator and an adaptive inertia weight to raise the search capacity, but also uses a new crowding operator to improve the distribution of nondominated solutions along the Pareto front, and uses the uniform design to obtain the optimal combination of the parameters of AMOPSO-II. Results show that AMOPSO-II has better exploratory capabilities than AMOPSO-I, and that the approach to multi-resolution image fusion based on AMOPSO-II realizes the Pareto optimal multi-resolution image fusion.
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