计算机工程2012，Vol.38Issue(24)：220-224,5.
一种基于PCNN的多聚焦图像融合改进算法
An Improved Multi-focus Image Fusion Algorithm Based on PCNN
摘要
Abstract
An improved multi-focus image fusion algorithm based on Pulse Coupled Neural Network(PCNN) is proposed for improving the fusion quality and the fusion efficiency. The image quality evaluation index of each block is calculated, which is selected with enough reason. The difference of the index is obtained by subtracting the two normalized indices. The difference of the index is input into PCNN model as external stimulus, and the output pulse is obtained. Comparing the value of output pulse with a given threshold, the fused image block is selected from the source image block whose evaluation index is large, while pulse output is larger than threshold. Take the source image block with small value of evaluation index. The performance of the proposed method is evaluated using six criteria including mutual information, cross entropy, root mean squared error, peak value signal-to-noise ratio, structure similarity index and correlation coefficient. Experimental result shows that the algorithm can improve image fusion effect.关键词
脉冲耦合神经网络/图像融合/融合质量/融合效率/外部刺激Key words
Pulse Coupled Neural Network(PCNN)/ image fusion/ fusion quality/ fusion efficiency/ external stimulus分类
信息技术与安全科学引用本文复制引用
童怀水,吴小俊..一种基于PCNN的多聚焦图像融合改进算法[J].计算机工程,2012,38(24):220-224,5.基金项目
国家自然科学基金资助项目(609730944) （609730944）
江西省自然科学基金资助项目(20114BAB201022) （20114BAB201022）
