A Novel Robust Zero-Watermarking Algorithm for Audio Based on Sparse Representation  

作　　者：Longting Xu Daiyu Huang Xing Guo Wei Rao Yunyun Ji Ruoyi Li Xiaochen Lu 

机构地区：[1]College of Information Science and Technology,Donghua University,Shanghai 200000,China [2]Tencent Ethereal Audio Lab,China

出　　处：《China Communications》2021年第8期237-248,共12页中国通信（英文版）

基　　金：the National Natural Science Foundation of China(No.62001100);the Fundamental Research Funds for the Central Universities(No.2232019D3-52);Shanghai Sailing Program.(No.19YF1402000).

摘　　要：Behind the prevalence of multimedia technology,digital copyright disputes are becoming increasingly serious.The digital watermarking prevention technique against the copyright infringement needs to be improved urgently.Among the proposed technologies,zero-watermarking has been favored recently.In order to improve the robustness of the zero-watermarking,a novel robust audio zerowatermarking method based on sparse representation is proposed.The proposed scheme is mainly based on the K-singular value decomposition(K-SVD)algorithm to construct an optimal over complete dictionary from the background audio signal.After that,the orthogonal matching pursuit(OMP)algorithm is used to calculate the sparse coefficient of the segmented test audio and generate the corresponding sparse coefficient matrix.Then,the mean value of absolute sparse coefficients in the sparse matrix of segmented speech is calculated and selected,and then comparing the mean absolute coefficient of segmented speech with the average value of the selected coefficients to realize the embedding of zero-watermarking.Experimental results show that the proposed audio zerowatermarking algorithm based on sparse representation performs effectively in resisting various common attacks.Compared with the baseline works,the proposed method has better robustness.

关 键 词：ZERO-WATERMARKING K-singular value decomposition dictionary learning sparse representtion 

分 类 号：TN912.3[电子电信—通信与信息系统] TP309.7[电子电信—信息与通信工程]