计算机工程与应用2017，Vol.53Issue(7)：177-180,4.DOI:10.3778/j.issn.1002-8331.1509-0099
脉冲耦合神经网络自适应图像融合算法研究
Adaptive image fusion algorithm based on pulse coupled neural networks
摘要
Abstract
As a new network model, Pulse Coupled Neural Networks(PCNN)has been widely used in many fields. Aiming at the insufficient of traditional image fusion by pulse coupled neural networks algorithm, a novel adaptive PCNN image fusion algorithm is proposed. Two features are used as external stimulus of PCNN to extract the complementary information of source images. The linking strength parameters of PCNN are determined adaptively according to contrast of source images. Through analyzing the traditional PCNN algorithms in obtaining the optimal fusion result, a novel method is proposed which can acquire the optimal fusion result by comparing the structural similarity of the fused image at each iteration. Experimental results for visible and infrared images show that the proposed algorithm is effective for image fusion.关键词
图像融合/脉冲耦合神经网络/结构相似度/客观评价Key words
image fusion/pulse coupled neural networks/structural similarity/objective evaluation分类
信息技术与安全科学引用本文复制引用
王红梅,付浩..脉冲耦合神经网络自适应图像融合算法研究[J].计算机工程与应用,2017,53(7):177-180,4.基金项目
国家自然科学基金(No.61401366) （No.61401366）
教育部留学回国人员启动基金 （）
航空科学基金(No.20150153001). （No.20150153001）
