基于四元数小波变换和Copula模型的图像融合

doi:10.11896/j.issn.1002-137X.2019.04.046

Abstract

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

CLC Number:

TP391

LI Kai, LUO Xiao-qing, ZHANG Zhan-cheng, WANG Jun. Image Fusion Using Quaternion Wavelet Transform and Copula Model[J].Computer Science, 2019, 46(4): 293-299.

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Image Fusion Using Quaternion Wavelet Transform and Copula Model

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