|本期目录/Table of Contents|

[1]李加恒,戴文战,李俊峰.基于互信息的多模态医学图像融合[J].浙江理工大学学报,2016,35-36(自科4):607-614.
 LI Jiaheng,DAI Wenzhan,LI Junfeng.Multimodality Medical Image Fusion Based on Mutual Information[J].Journal of Zhejiang Sci-Tech University,2016,35-36(自科4):607-614.
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基于互信息的多模态医学图像融合()
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浙江理工大学学报[ISSN:1673-3851/CN:33-1338/TS]

卷:
第35-36卷
期数:
2016年自科4期
页码:
607-614
栏目:
出版日期:
2016-07-10

文章信息/Info

Title:
Multimodality Medical Image Fusion Based on Mutual Information
文章编号:
1673-3851 (2016) 04-0607-08
作者:
李加恒戴文战李俊峰
1.浙江理工大学自动化研究所,杭州 310012; 2.浙江工商大学信息与电子工程学院,杭州 310012
Author(s):
LI Jiaheng DAI Wenzhan LI Junfeng
1. Institute of Automation, Zhejiang Sci-Tech University, Hangzhou 310012, China; 2. School of  Information and Electronic, Zhejiang Gongshang University, Hangzhou 310012, China
关键词:
医学图像融合提升小波变换互信息区域梯度能量区域标准差
分类号:
TP391
文献标志码:
A
摘要:
目前已知的医学图像融合算法未充分考虑源图像间差异性的大小,针对该不足提出了一种基于互信息特征的多模态融合算法。算法引入提升小波变换,将目标图像分解为高、低频子带,根据高频子带的互信息量不同,对低互信息子带采用区域梯度能量与区域标准差相结合的融合规则,对高互信息子带采用边缘强度取大的融合规则。通过多组目标图像融合对比的实验进行验证,算法融合得到的图像信息丰富,边缘清晰,具有良好的视觉特性和优秀的评价指标。

参考文献/References:

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相似文献/References:

[1]徐卫良,戴文战,李俊峰.基于提升小波变换和PCNN的医学图像融合算法[J].浙江理工大学学报,2016,35-36(自科6):891.
 XU Weiliang,DAI Wenzhan,LI Junfeng.Medical Image Fusion Algorithm Based on Lifting Wavelet  Transform and PCNN[J].Journal of Zhejiang Sci-Tech University,2016,35-36(自科4):891.
[2]殷鑫华,戴文战,李俊峰.基于在线字典学习的自适应医学图像融合算法[J].浙江理工大学学报,2017,37-38(自科2):246.
 YIN Xinhua,DAI Wenzhan,LI Junfen.Adaptive Medical Image Fusion Algorithm Based onOnline Dictionary Learning[J].Journal of Zhejiang Sci-Tech University,2017,37-38(自科4):246.
[3]潘树伟,戴文战,李俊峰.基于纹理特征与广义相关性结构信息的医学图像融合[J].浙江理工大学学报,2017,37-38(自科3):423.
 PAN Shuwei,DAI Wenzhan,LI Junfeng.Medical Image Fusion Algorithm Based on Textural Features and Generalized Correlation Structure Information[J].Journal of Zhejiang Sci-Tech University,2017,37-38(自科4):423.

备注/Memo

备注/Memo:
收稿日期: 2015-09-19
基金项目: 国家自然科学基金项目(61374022)
作者简介: 李加恒(1990-),男,江苏连云港人,硕士研究生,主要从事图像处理方面的研究
通信作者: 戴文战,E-ail:dwz@zjsu.edu.cn
更新日期/Last Update: 2016-09-13