改进多目标粒子群优化算法及在图像融合中的应用

Image Fusion based on an improved algorithm of Multi-objective Particle swarm Optimization

在深入研究图像融合算法的基础上,受多目标粒子群优化算法(MOPSO)的启发,提出了一种改进的MOPSO算法,并将该改进算法用于图像融合方面。这种算法提出了两次调节指数收敛函数,使得寻优速率得到更为平滑地过渡,从而让搜索结果更好的接近Pareto最优解集。实验结果表明,与传统的融合算法比较在客观性能指标上得到提高。

Through studying and simulating the traditional algorithm of image fusion and Inspiring by the multi-objective particle swarm optimization,we proposing an improved algorithm of MOPSO.The new algorithm based on multi-objective particle swarm algorithm framework.However,there are some differences between them.The new algorithm adopts more effective ways of speed changing and multi-objective choice processing which makes better performance and the searching solutions closing to the Pareto optimal solution set.The new algorithm has been used for remote sensing images fusion and multi-focus images fusion,which have achieved better results.