|本期目录/Table of Contents|

[1]陈杰,茅剑,张杰敏.一种基于形态分量的多聚焦图像融合算法[J].集美大学学报(自然科学版),2019,24(1):68-75.
　CHEN Jie,MAO Jian,ZHANG Jiemin.A Novel Algorithm for Multi-fosus Image Fusion Based on Morphological Component[J].Journal of Jimei University,2019,24(1):68-75.
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一种基于形态分量的多聚焦图像融合算法(PDF)
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《集美大学学报（自然科学版）》[ISSN:1007-7405/CN:35-1186/N]

卷:
第24卷
期数:
2019年第1期
页码:
68-75
栏目:
数理科学与信息工程
出版日期:
2019-01-28

文章信息/Info

Title:
A Novel Algorithm for Multi-fosus Image Fusion Based on Morphological Component
作者:
陈杰; 茅剑; 张杰敏
(集美大学计算机工程学院，福建 厦门 361021)
Author(s):
CHEN Jie; MAO Jian; ZHANG Jiemin
(Computer Engineering College，Jimei University，Xiamen 361021，China)
关键词:
图像融合; 形态分量; curvelet变换; 高斯差分算子; 特征活跃度; 细节信息
Keywords:
image fusion; morphological component; curvelet transform; difference operator of Gaussian; feature activity; details information
分类号:
-
DOI:
-
文献标志码:
A
摘要:
提出一种基于形态分量思想的多聚焦图像融合算法。该方法首先对源图像迭代分解，将其分解为低频和高频两个分量，并用curvelet变换表示低频分量，然后，对低频分量采用高斯差分算子定义图像点的特征活跃度和融合规则，对高频分量的细节特征度量采用加权梯度差的方法来衡量和融合。仿真实验在四组多聚焦图像中进行，除了与传统的图像融合算法做比较外，还与系数绝对值最大法的融合算法进行比较。实验结果表明：该方法在平均梯度、空间频率、信息熵等指标上优于传统的图像融合方法，同时也优于基于系数绝对值最大法的融合规则。
Abstract:
This paper presents a multi-focus image fusion algorithm based on morphological component.Firstly，source images are decomposed into low-frequent components and high-frequent components by iteration，and curvelet transformation is used for low-frequent components.Secondly，the low-frequent components are fused by applying a rule of feature activity which is defined by using the operator of difference of Gaussian，and the high frequent components are fused by means of a rule of details information which is defined by using weighted gradient.Finally,simulation experiments are conducted through four groups of multi-focus images.The experimental results compared with ones by traditional image fusion algorithm and the algorithm of the max absolute value of component coefficients.The experimental results show that the proposed algorithm outperforms other approaches in terms of average gradient，space frequence and entroy .

参考文献/References:

相似文献/References:

[1]彭文竹,王钦,吴亚建,等.基于偏振特性的雾霾降质图像融合复原方法[J].集美大学学报(自然科学版),2017,22(3):60.
　PENG Wenzhu,WANG Qin,WU Yajian,et al.Image Fusion Restoration Algorithm Based on Polarization Characteristics of Haze[J].Journal of Jimei University,2017,22(1):60.

备注/Memo

备注/Memo:
更新日期/Last Update: 2019-03-10