论文标题
使用基于图的变换和单数值分解的强大音频水印
Robust Audio Watermarking Using Graph-based Transform and Singular Value Decomposition
论文作者
论文摘要
基于图的转换（GT）最近已成功地利用了信号处理域，特别是用于压缩目的。在本文中，我们采用了GBT以及奇异的值分解（SVD），目的是提高音频水印与对音频信号的不同攻击（例如噪声和压缩）的鲁棒性。 Noizeus语音数据库和Mir-1K音乐数据库的实验结果清楚地证明了所提出的基于GBT-SVD的方法对攻击是可靠的。此外，根据PSNR，PESQ和Stoi测量，结果在嵌入后表现出良好的质量。同样，提出的方法的有效载荷分别为语音和音乐信号的800和1600，它们比某些强大的水印方法（例如DWT-SVD和DWT-DCT）高。
Graph-based Transform (GT) has been recently leveraged successfully in the signal processing domain, specifically for compression purposes. In this paper, we employ the GBT, as well as the Singular Value Decomposition (SVD) with the goal to improve the robustness of audio watermarking against different attacks on the audio signals, such as noise and compression. Experimental results on the NOIZEUS speech database and MIR-1k music database clearly certify that the proposed GBT-SVD-based method is robust against the attacks. Moreover, the results exhibit a good quality after the embedding based on PSNR, PESQ, and STOI measures. Also, the payload for the proposed method is 800 and 1600 for speech and music signals, respectively which are higher than some robust watermarking methods such as DWT-SVD and DWT-DCT.
