[1]吴粉侠,段群. 基于NSCT的PCA与PCNN相结合的图像融合算法[J].计算机技术与发展,2015,25(12):72-75.
　WU Fen-xia,DUAN Qun. Image Fusion Algorithm Combining PCNN and PCA Based on NSCT[J].,2015,25(12):72-75.
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 基于NSCT的PCA与PCNN相结合的图像融合算法()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
25
期数:
2015年12期
页码:
72-75
栏目:
智能、算法、系统工程
出版日期:
2015-12-10

文章信息/Info

Title:
 Image Fusion Algorithm Combining PCNN and PCA Based on NSCT
文章编号:
1673-629X（2015)12-0072-04
作者:
 吴粉侠; 段群
 咸阳师范学院 图形图像研究所
Author(s):
 WU Fen-xia; DUAN Qun
关键词:
 ; 图像融合; 非采样Contourlet变换; 脉冲耦合神经网络; 主成分分析
Keywords:
 ; image fusion; NSCT; PCNN; PCA
分类号:
TP391.4
文献标志码:
A
摘要:
 为了克服小波变换与Contourlet变换在图像融合应用中的不足,文中提出了一种基于非下采样Contourlet变换(Non-Subsampled Contourlet Transform,NSCT)与主成分分析(Principal Component analysis)及脉冲耦合神经网络(Pulse-Coupled Neural Networks,PCNN)相结合的融合算法. 首先对被融合图像执行NSCT分解,将图像分解为一个低频子带图像和多个高频子带图像,利用PCa加权规则融合低频子带图像得到融合图像的低频子带图像,利用PCNN规则融合各高频子带图像得到融合图像的高频子带图像,最后经NSCT逆变换重构图像. 实验结果表明,该算法有效地融合了源图像中的重要信息,融合图像边缘、纹理、细节清晰,得到了较好的视觉效果和较优的评价指标.
Abstract:
 Toovercome the shortage of wavelet transformation and Contourlet transformation in image fusion,a novel algorithm is pro-posed combining Non-Subsampled Contourlet Transform (NSCT),Principal Component Analysis (PCA) and Pulse-Coupled Neural Networks ( PCNN) . The registered images are decomposed by NSCT,which can obtain the low-frequency subimages and a series high-frequency subimages. The rule of PCA is applied to the low-frequency subimage. And the rule of PCNN is applied to the high-frequency subimages. Then the fusion image is obtained by inverse NSCT. Experimental results show that the proposed method can retain a visual quality and objective evaluation index,and performs some related fusion approaches.

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更新日期/Last Update: 2016-01-28