期刊名称：International Journal of Multimedia and Ubiquitous Engineering
印刷版ISSN：1975-0080
出版年度：2007
卷号：2
期号：3
出版社：SERSC
摘要：The particle swarm optimization (PSO) is a new swarm intelligence technique inspired by social behavior of bird flocking. In this paper, the optimal multi-objective particle swarm optimization (OMOPSO) is presented. Since the parameters determine the optimization performance of the algorithm, the uniform design is introduced to obtain the optimal combination of the parameters. Additionally, a new crowding operator is used to improve the
-dominance is used to fix the size of the set of final solutions. OMOPSO is applied to optimize the parameters of blind color image fusion. First the model of blind color image fusion in YUV color space is established, and then the proper evaluation metrics without the reference image are given, in which a new metrics of conditional mutual information is proposed. Experimental results indicate that the method of blind color image fusion based on OMOPSO realizes the Pareto optimal blind color image fusion.
