An adaptive multi-objective particle swarm optimization for color image fusion

Authors:
Yifeng Niu;Lincheng Shen
Affiliations:
College of Mechatronic Engineering and Automation, National University of Defense Technology, Changsha, China;College of Mechatronic Engineering and Automation, National University of Defense Technology, Changsha, China
Venue:
SEAL'06 Proceedings of the 6th international conference on Simulated Evolution And Learning
Year:
2006

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Abstract

A novel algorithm of adaptive multi-objective particle swarm optimization (AMOPSO-II) is proposed and used to search the optimal color image fusion parameters, which can achieve the optimal fusion indices. First the algorithm of AMOPSO-II is designed; then the model of color image fusion in YUV color space is established, and the proper evaluation indices are given; and finally AMOPSO-II is used to search the optimal fusion parameters. AMOPSO-II 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. Experimental results indicate that AMOPSO-II has better exploratory capabilities than MOPSO and AMOPSO-I, and that the approach to color image fusion based on AMOPSO-II realizes the Pareto optimal color image fusion.