计算机科学 ›› 2019, Vol. 46 ›› Issue (4): 293-299.doi: 10.11896/j.issn.1002-137X.2019.04.046

• 图形图像与模式识别 • 上一篇    下一篇

基于四元数小波变换和Copula模型的图像融合

李凯1,2, 罗晓清1,2, 张战成3, 王骏4   

  1. 江苏省模式识别与计算智能工程实验室 江苏 无锡2141221
    江南大学物联网工程学院 江苏 无锡2141222
    苏州科技大学电子与信息工程学院 江苏 苏州2150003
    江南大学数字媒体学院 江苏 无锡 2141224
  • 收稿日期:2018-06-01 出版日期:2019-04-15 发布日期:2019-04-23
  • 通讯作者: 罗晓清(1980-),女,博士,副教授,CCF会员,主要研究方向为模式识别与图像处理,E-mail:xqluo@jiangnan.edu.cn(通信作者)
  • 作者简介:李 凯(1994-),女,硕士生,主要研究方向为模式识别与图像处理,E-mail:1009044970@qq.com;张战成(1977-),男,博士,副教授,主要研究方向为模式识别与图像处理;王 骏(1978-),男,博士,副教授,主要研究方向为模式识别与图像处理。
  • 基金资助:
    本文受国家自然科学基金(61772237),江苏省自然科学基金(BK20151358,BK20151202),总装教育部联合预研项目(6141A02033312),苏州市应用基础研究计划(SYG201702),中央高校自主科研项目(JUSRP51618B)资助。

Image Fusion Using Quaternion Wavelet Transform and Copula Model

LI Kai1,2, LUO Xiao-qing1,2, ZHANG Zhan-cheng3, WANG Jun4   

  1. Jiangsu Laboratory of Pattern Recognition and Computational Intelligence,Wuxi,Jiangsu 214122,China1
    School of IoT Engineering,Jiangnan University,Wuxi,Jiangsu 214122,China2
    School of Electronics and Information Engineering,Suzhou University of Science and Technology,Suzhou,Jiangsu 215000,China3
    School of Digital Media,Jiangnan University,Wuxi,Jiangsu 214122,China4
  • Received:2018-06-01 Online:2019-04-15 Published:2019-04-23

摘要: 四元数小波变换是一种既能够提供幅值又能够提供相位信息的新型多尺度变换工具。文中通过Copula模型捕获四元数小波变换系数的相关性,提出了一种基于四元数小波变换和Copula模型的图像融合算法。该算法首先对待融合图像进行四元数小波分解,接着通过构建Copula模型捕获高频子带幅度相位及低频对应相位之间的相关性,然后提取高频子带系数特征,即Copula联合概率密度的区域能量、相位梯度、系数能量和局部对比度。通过这些特征构建综合特征,并将该特征作为高频活动测度,采用综合特征取大的融合规则实现高频子带的融合;低频子带结合低频相位梯度和相位局部方差得到综合特征,将该特征作为低频活动测度,然后通过取大的融合规则实现低频子带的融合。最后使用逆四元数小波变换得到融合图像。实验结果表明,与传统融合算法相比,所提算法在主观和客观方面均取得了较佳的融合效果。

关键词: Copula模型, 幅度相位, 四元数小波, 图像融合

Abstract: Quaternion wavelet transform (QWT) is a new multi-scale transform tool which can provide both amplitude and phase information.In this paper,copula model is used to capture the correlation of QWT coefficients,and a novel image fusion method based on QWT and Copula modelwas proposed.First,QWT is performed on the source images.Second,the dependency among the magnitude-phase of high frequency subbands and the corresponding phase of low frequency phase is established by Copula models.Next,a choose-max fusion rule based on the comprehensive feature constructed by the regional energy of Copula joint probability density,the gradient of phases,the QWT coefficient energy and the local contrast,is proposed for high frequency subbands.A choose-max fusion rule based on the comprehensive feature constructed by gradient and local variance of low frequency phases is proposed for low frequency subbands.Finally,the fusion image is obtained by inverse QWT.Experimental results demonstrate that the performance of the proposed method is superior to the traditional fusion methods.

Key words: Copula model, Image fusion, Magnitude-phase, Quaternions wavelet transform

中图分类号: 

  • TP391
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