Multi-focus image fusion using pulse coupled neural network
Multi-focus image fusion using pulse coupled neural network
复制标题
使用脉冲耦合神经网络的多焦点图像融合
DOI：
10.1016/j.patrec.2007.01.013
复制
发表时间：
2007-07-01
影响因子：
5.1
通讯作者：
Jing, Zhongliang
中科院分区：
文献类型：
--
作者：
Huang, Wei;Jing, Zhongliang
提出了一种基于脉冲耦合神经网络（PCNN）的多聚焦图像融合方法。首先将配准的源图像分解为块，图像块的大小为8 x 8像素。通过计算每个块的图像拉普拉斯算子的能量来获得特征图。将特征图作为外部刺激输入PCNN。通过比较PCNN的输出，从源图像中选择图像块，可以构建最终的融合图像。实验结果表明，该方法在视觉效果和客观评价标准方面均优于已有的融合方法。(c)2007 Elsevier B.V.保留所有权利。
This paper presents a method for multi-focus image fusion by using pulse coupled neural network (PCNN). The registered source images are first decomposed into blocks and the size of the image blocks is 8 x 8 pixels. Feature maps are obtained by computing the energy of image Laplacian of each block. Input the feature maps into PCNN as external stimulus. The final fused image can be constructed by selecting the image blocks from the source images based on the comparison of the outputs of the PCNN. Experimental results show that the proposed method outperforms some previous fusion methods, both in visual effect and objective evaluation criteria. (c) 2007 Elsevier B.V. All rights reserved.