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OALib Journal期刊
ISSN: 2333-9721
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Image Fusion Based on Quantum-behaved Particle Swarm Optimization Algorithms
基于QPSO的图像融合算法的研究*

Keywords: QPSO algorithm,optimization,pixel,image fusion
基于量子行为的粒子群优化算法
,优化,像素,图像融合,图像融合算法,研究,Optimization,Algorithms,Swarm,Particle,Based,Fusion,效果,比较,遗传算法,全局收敛,解空间,覆盖,空间能,取样,迭代,数个数,优化问题,融合方法,粒子群优化算法

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Abstract:

The paper proposed an image fusion approach based on QPSO algorithm.Formulated the image fusion problem as an optimization problem and adopt Quantum-behaved Particle Swarm Optimization algorithm to solve the problem.Not only QPSO has less parameters to control,but also does its sampling space at each iteration covers the whole solution space.Thus QPSO can find the best solution quickly and guarantee to be global convergent.Genetic Algorithm(GA) and Particle Swarm Optimization(PSO) were tested for performance comparison with QPSO,and the result showed the good efficiency of QPSO algorithms to image fusion.

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