Multi-resolution Image Fusion Using AMOPSO-II

  • Yifeng Niu
  • Lincheng Shen
Part of the Lecture Notes in Control and Information Sciences book series (LNCIS, volume 345)


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.


Particle Swarm Optimization Discrete Wavelet Transform Pareto Front Image Fusion Nondominated Solution 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Yifeng Niu
    • 1
  • Lincheng Shen
    • 1
  1. 1.School of Mechatronics and AutomationNational University of Defense TechnologyChangshaChina

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