Image registration based on a novel culture particle swarm optimization
This paper designed a kind of optimization algorithm for image registration.By combining with cultural particle swarm optimization (CPSO),a novel image registration algorithm is outlined in this paper.In the algorithm,the search space was divided into two spaces,group space and belief space.In the algorithm,the search space was divided into two spaces,group space and belief space.Group space is the main space and evolved with self-adapted PSO.Particles of group space not only track individual extrema and global extrema to update themselves,but also exchange with the best individuals in belief space to speed up the convergence rate,which overcome the problems in image registration such as the large computation complexity,slow search speed and so on.A wealth of tests show that the proposed algorithm has better registration accuracy and robustness compared with existing PSO registration algorithm.
Culture particle swarm optimization Image registration Mutual information Measure function
Xia Zhu Renwen Chen
State Key Laboratory of Mechanics and Control of Mechanical Structures,Nanjing University of Aeronau State Key Laboratory of Mechanics and Control of Mechanical Structures,Nanjing University of Aeronau
国内会议
济南
英文
1-8
2014-10-16（万方平台首次上网日期，不代表论文的发表时间）