基于EMD的音频水印算法研究

提出了一种基于经验模态分解(Empirical Mode Decomposition,EMD)的音频水印算法,选择EMD分解得到的冗余信号分量作为水印的嵌入位置,并证明了冗余信号分量按照提出的算法嵌入水印以后仍然是冗余信号分量,从而为水印嵌入提取提供了理论基础.通过粒子群优化算法求解出适用于EMD分解的最优音频水印嵌入强度,按此强度嵌入水印,可以同时满足水印的健壮性和不可感知性.仿真结果表明,使用计算出的最优嵌入强度嵌入水印,嵌入水印后的音频信号在受到大部分攻击的情况下可以确保水印的不可见性和健壮性.

Research on Audio Watermarking Algorithm Based on EMD

An audio watermarking algorithm based on EMD(Empirical Mode Decomposition) was proposed.Residual signal components decomposed from EMD were selected to embed watermark by the proposed algorithm and the watermarked components are proved to be still residual signal components,which provides the theoretical basis for the watermark embedding and extraction.The optimal audio watermark embedding strength in EMD was solved by particle swarm optimization algorithm.The robustness and imperceptibility of watermarking can be satisfied according to this embedding strength.The simulation results show that using the optimal embedding strength to embed watermark can guarantee the imperceptibility and robustness of the watermark in most attack conditions.