关键词: 图像融合, 脉冲耦合神经网络, 果蝇优化算法, 平均结构相似度

Abstract: An adaptive fusion algorithm based on Pulse Coupled Neural Networks（PCNN） and Fruit Fly Optimization Algorithm（FOA） is proposed in order to overcome the difficulty of parameters selection of PCNN. The mean structure similarity is used as fitness function of FOA and the global search ability of FOA is used to set four parameters of PCNN. The source images are fused by PCNN with maximum principle. The experimental results demonstrate that the proposed method outperforms the other methods in term of visual evaluation and objective evaluation.

Key words: image fusion, Pulse Coupled Neural Networks（PCNN）, Fruit Fly Optimization Algorithm（FOA）, mean structural similarity