Infrared Image Contrast Enhancement Based on Modified Particle Swarm Optimization

摘要：

　　Adaptive infrared image contrast enhancement is presented based on modified particle swarm optimization (PSO) and incomplete Beta Function.On the basis of traditional PSO,modified PSO integrates into the theory of Multi-Particle Swarm and evolution theory algorithm.By using separate search space optimal solution of multiple particles,the global search ability is improved.And in the iteration procedures,timely adjustment of acceleration coefficients is convenient for PSO to find the global optimal solution in the later iteration.Through infrared image simulation,experimental results show that the modified PSO is better than the standard PSO in computing speed and convergence.

关键词： Particle Swarm Optimization Evolutionary Computation Infrared Image Contrast Enhancement Incomplete Beta Function

作者: Rentao Zhao Youyu Wang Huade Li Jun Tie

作者单位: School of Automation and Electrical Engineering,University of Science & Technology Beijing,Beijing,1 North China University of Technology,Beijing,100041,China School of Automation and Electrical Engineering,University of Science & Technology Beijing,Beijing,1

会议类型: 国际会议

会议名称: 2013 2nd international Conference on Opto-Electronics Engineering and Materials Eesearch(2013第二届光电工程与材料研究国际会议)(OEMR2013)

会议地点: 郑州

会议语种:英文

页码: 342-346

在线出版日期: 2013-10-19（万方平台首次上网日期，不代表论文的发表时间）