基于多相关HMT模型的DT CWT域数字水印算法  

A Blind Watermark Decoder in DT CWT Domain Using Weibull Distribution-Based Vector HMT Model

作　　者：王向阳[1] 牛盼盼[1] 杨红颖[1] 李丽[1] WANG Xiang-Yang;NIU Pan-Pan;YANG Hong-Ying;LI Li(School of Computer and Information Technology,Liaoning Normal University,Dalian 116029)

机构地区：[1]辽宁师范大学计算机与信息技术学院,大连116029

出　　处：《自动化学报》2021年第12期2857-2869,共13页Acta Automatica Sinica

基　　金：国家自然科学基金(61472171,61701212);中国博士后科学基金(2018T110220);辽宁省教育厅科学研究经费项目(面上项目)(LJKZ0985);辽宁省自然科学基金(2019-ZD-0468)资助。

摘　　要：本文以双树复数小波变换(Dual-tree complex wavelet transform,DT CWT)及隐马尔科夫树(Hidden Markov tree,HMT)理论为基础,提出了一种基于Weibull向量HMT模型的DT CWT域数字音频盲水印算法.原始数字音频首先进行DT CWT,然后利用局部信息熵刻画音频内容特征并据此确定出重要DT CWT系数段,进而将水印信息乘性嵌入到重要DT CWT高频系数幅值内.水印检测时,首先根据DT CWT系数幅值的边缘分布及系数间的多种相关性(包括子带内、尺度间、分解树间等相关性),构造出Weibull混合向量HMT统计模型,并估计出其统计模型参数;然后,利用局部最大势能(Locally most powerful,LMP)检验理论构造出局部最优检测器(Locally optimum decoder,LOD)以盲提取水印信息.仿真实验结果表明,本文算法可以较好地获得不可感知性、鲁棒性、水印容量之间的良好平衡,其总体性能优于现有同类音频水印算法.In this paper,we propose a blind audio watermark decoder in dual-tree complex wavelet transform(DT CWT)domain,wherein the Weibull distribution-based vector hidden Markov tree(HMT)model is used.In the proposed watermarking approach,the DT CWT is firstly performed on the original host audio,then the significant DT CWT coefficient segments are determined according to local information entropy,and finally the watermark data is embedded into the significant high-frequency coefficient amplitudes in the DT CWT domain.At the watermark receiver,DT CWT highpass coefficient amplitudes are firstly modeled by employing the Weibull distribution-based vector HMT Model,where both the local statistical properties and various dependencies of the DT CWT coefficients are captured.Then the parameters of the Weibull distribution-based vector HMT model are estimated on the highpass coefficients of digital audio using the maximum likelihood estimation(MLE).And finally,by employing locally most powerful test and the Weibull distribution-based vector HMT model,a blind local optimum decoder(LOD)is developed.We conduct extensive experiments to evaluate the performance of the proposed blind watermark decoder,in which encouraging results validate the effectiveness of the proposed technique.

关 键 词：音频水印 向量隐马尔科夫树 Weibull混合模型 局部信息熵 双树复数小波变换 局部最优检测器 

分 类 号：TP309.7[自动化与计算机技术—计算机系统结构]