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A blind audio watermarking algorithm by logarithmic quantization index modulation

机译:对数量化指标调制的盲音频水印算法

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摘要

In this paper we present a blind audio watermarking algorithm based on the vector norm and the logarithmic quantization index modulation (LQIM) in the wavelet domain, integrating the robustness of the vector norm with the imperceptibility of the logarithmic quantization index modulation based on μ-Law (or mu-Law) companding. Firstly μ-Law companding is adopted to transform the vector norm of the segmented wavelet approximation components of the original audio signal. And then a binary image scrambled by the chaotic sequence as watermark is embedded in the transformed domain with a uniform quantization scheme. Experimental results demonstrate that even if the capacity of the proposed algorithm is high, up to 102.4 bps, this algorithm can still maintain a high quality of the audio signal, and achieve a better performance, such as imperceptibility, robustness and complexity in comparison with the uniform quantization based algorithms against common attacks. What's more, it can resist amplitude scaling attack effectively.
机译:本文提出了一种基于矢量范数和小波域对数量化指标调制(LQIM)的盲音频水印算法,将矢量范数的鲁棒性与基于μ律的对数量化指标调制的不可感知性相结合(或mu-Law)压扩。首先,采用μ-Law压扩来转换原始音频信号的分段小波逼近分量的矢量范数。然后,以统一的量化方案将以混沌序列作为水印加扰的二进制图像嵌入到转换后的域中。实验结果表明,即使所提算法的容量很高,高达102.4 bps,该算法仍能保持较高的音频信号质量,与传统算法相比,具有更好的感知度,鲁棒性和复杂度。基于统一量化的针对常见攻击的算法。而且,它可以有效地抵抗幅度缩放攻击。

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