利用抖动量化和信噪比的自适应鲁棒音频盲水印算法

An Adaptive Robust Audio Blind Watermarking Algorithm Using Dithering Quantization and SNR

提出了基于抖动量化和信噪比(SNR)的自适应鲁棒音频盲水印算法。在分析经典量化方法存在的安全问题的基础上,提出了抖动量化嵌入和提取水印的方法,抖动量由密钥控制的混沌通过映射产生,加强了系统的安全性。针对现有水印算法需通过反复实验确定合适嵌入强度的问题,算法基于音频内容的信噪比公式自适应地计算水印嵌入强度。实验表明,本算法是不可听的,对常规信号处理操作是鲁棒的。

An adaptive robust audio blind watermarking algorithm based dither quantization and signal to noise ratio is proposed.Based on analyzing open secure question of classical quantization means,dithering quantization is proposed to embed and extract watermarking.Dithering vector is generated by mapping chaos sequences which is controlled by keys,so system security is improved.To aiming at the problem of existing watermarking algorithms to ascertain the appropriate strength by repeating experiment or experiential data,the proposed algorithm calculates adaptively watermarking strength by SNR formula based on audio content.Experimental results prove the proposed algorithm is inaudible and robust for common signal process manipulations.