摘要
The paper proposes a robust digital audio watermarking scheme using blind source separation(BSS) based on the global optimization of independency metric(IM),which is formulated as a generalized eigenvalue(GE) problem.Compared with traditional information-theoretical approaches used in digital audio watermarking,such as fast independent component analysis(FastICA),the proposed scheme has lower complexity without timeconsuming iteration steps used in FastICA.To make full use of the multiresolution characteristic of discrete wavelet transform(DWT) and the energy compression characteristic of discrete cosine transform(DCT),the watermark is embedded in the middle DWT-DCT coefficients and the independent component analysis(ICA) approach based on IM is used in the detecting scheme.Simulation results based on Stirmark for Audio v02 show that the proposed scheme has strong robustness as well as the imperceptibility and security.
The paper proposes a robust digital audio watermarking scheme using blind source separation （BSS） based on the global optimization of independency metric （IM）, which is formulated as a generalized eigenvalue （GE） problem. Compared with traditional information-theoretical approaches used in digital audio watermarking, such as fast independent component analysis （FastICA）, the proposed scheme has lower complexity without timeconsuming iteration steps used in FastICA. To make full use of the multiresolution characteristic of discrete wavelet transform （DWT） and the energy compression characteristic of discrete cosine transform （DCT）, the watermark is embedded in the middle DWT-DCT coefficients and the independent component analysis （ICA） approach based on IM is used in the detecting scheme. Simulation results based on Stirmark for Audio v02 show that the proposed scheme has strong robustness as well as the imperceptibility and security.
基金
the Scientific Research Foundation for the Returned Overseas Chinese Scholars,State Education Ministry of China
the National Natural Science Foundation of China (No. 60802058)
