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Volume 30 Issue 3
Dec.  2010
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Yang Yan-xi, Liu Ding, Xin Jing. Research of Image Correlation Matching Method Based on CPSO[J]. Journal of Electronics & Information Technology, 2008, 30(3): 529-533. doi: 10.3724/SP.J.1146.2006.01344
Citation: Yang Yan-xi, Liu Ding, Xin Jing. Research of Image Correlation Matching Method Based on CPSO[J]. Journal of Electronics & Information Technology, 2008, 30(3): 529-533. doi: 10.3724/SP.J.1146.2006.01344

Research of Image Correlation Matching Method Based on CPSO

doi: 10.3724/SP.J.1146.2006.01344 cstr: 32379.14.SP.J.1146.2006.01344
  • Received Date: 2006-09-07
  • Rev Recd Date: 2007-01-24
  • Publish Date: 2008-03-19
  • A Chaos Particle Swarm Optimization (CPSO) algorithm is presented. The initial location of the particle is evaluated by chaos. During the running time, according to the variance of the populations fitness, the chaotic location update of the particle is performed adaptively. The experimental results using the testing functions show that CPSO is able to search the global optimizer and avoiding the premature convergence on the multidimensional variable space. Applied the algorithm to image correlation matching, a new image correlation matching method based on CPSO is presented. The experimental results show that this method is very effective for image matching processing with noise.
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  • Chalermwat P, El-Ghazawi T, and Le Moigne J. Two-phasegenetic algorithm-based image registration on parallelclusters [J].Journal of Future Generation ComputingSystems.2001, 17(3):467-476[2]Brumby S, Theiler J, and Perkins S, et al.. Investigation offeature extraction by a genetic algorithm[R]. in Proc. 1999,SPIE 3812: 24-31.[3]徐建斌, 洪文, 吴一戎. 一种基于距离变换和遗传算法的遥感图像匹配算法[J].电子与信息学报.2005, 27(7):1009-1012浏览[4]熊兴华, 钱增波, 王任享. 遗传算法与最小二乘相结合的遥感图像子像素匹配[J]. 测绘学报, 2001(30), 1: 54-59.Xiong Xing-hua, Qian Zeng-bo, and Wang Ren-xiang. Aremote sensing image subpixel matching combined geneticalgorithm with least square matching[J]. Acta Geodaetica EtCartographic Sinica, 2001(30), 1: 54-59.[5]Kennedy J and Eberhart R. Particle swarm optimization[R].Proc. IEEE Int. Conf. on Neural Networks, IV, Piscataway,NJ: IEEE Service Center, 1995: 1942-1948.[6]Shi Y H and Eberhart R C. Parameter selection in particleswarm optimization[R]. In proc. of the 7th Annual Conf. onEvolutionary Programming, New York, 1998: 591-600.[7]Angeline P J. Using selection to improve particle swarmoptimization[R]. Proceedings of the IEEE Congress onEvolutionary Computation, Anchorage, Alaska, May 4-9,1998: 84-89.[8]Clerc M. The swarm and queen: Towards a deterministicand adaptive particle swarm optimization[R]. Proceedingsof the IEEE Congress on Evolutionary Computation,Washington, DC, 1999: 1951-1957.[9]杨俊杰, 周建中, 喻菁等. 基于混沌搜索的粒子群优化算法[J].计算机工程与应用, 2005(16): 69-71.Yang Jun-jie, Zhou Jian-zhong, and Yu Jing, et al.. Particleswarm optimization algorithm based on chaos searching[J].Computer Engineering and Applications, 2005(16): 69-71.[10]唐巍, 郭镇明, 唐嘉亨等. 复杂函数优化的混沌遗传算法[J].哈尔滨工程大学学报, 2000, 21(5): 1-5.Tang Wei, Guo Zhenming, and Tang Jiaheng, et al..Optimizing complex functions by chaos genetic algorithm[J].Journal of Harbin Engineering University, 2000, 21(5):1-5.[11]刘永红. 图像匹配时矩的高效算法[J].信号处理, 1996,12(4): 356-361.Liu Yong-hong. A high efficient image moments matchingalgorithm [J]. Signal Processing, 1996, 12(4): 356-361.
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