基于差分进化优化的鲁棒svd音频水印方案

B. Lei, I. Soon, Ee-Leng Tan
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引用次数: 106

摘要

提出了一种基于奇异值分解(SVD)和差分进化(DE)的基于抖动调制(DM)量化算法的鲁棒音频水印方案。针对音频版权保护问题,提出了提升小波变换-离散余弦变换-SVD算法和离散小波变换-DCT-SVD算法。在我们的方法中,首先使用LWT\DWT对主信号进行分解并获得相应的近似系数,然后使用DCT来利用“能量压缩”的特性。进一步进行奇异值分解,获取奇异值,增强方案的鲁棒性。采用自适应DM量化对奇异值进行量化并嵌入水印。为了抵御去同步攻击,使用音频统计特征插入同步代码。此外,该算法还有效地解决了鲁棒性和不可感知性的冲突问题。仿真结果表明,LWT-DCT-SVD和DWT-DCT-SVD方法不仅具有良好的不可感知性能,而且能够抵抗一般的信号处理、混合攻击和去同步攻击。与以往的DWT-DCT、支持向量回归(SVR)-DWT-DCT和DWT-SVD方法相比,我们的方法对所选攻击具有更强的鲁棒性。
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Robust SVD-Based Audio Watermarking Scheme With Differential Evolution Optimization
In this paper, a robust audio watermarking scheme based on singular value decomposition (SVD) and differential evolution (DE) using dither modulation (DM) quantization algorithm is proposed. Two novel SVD-based algorithms, lifting wavelet transform (LWT)-discrete cosine transform (DCT)-SVD and discrete wavelet transform (DWT)-DCT-SVD, are developed for audio copyright protection. In our method, LWT\DWT is first applied to decompose the host signal and obtain the corresponding approximate coefficients followed by DCT to take advantage of “energy compaction” property. SVD is further performed to acquire the singular values and enhance the robustness of the scheme. The adaptive DM quantization is adopted to quantize the singular values and embed the watermark. To withstand desynchronization attacks, synchronization code is inserted using audio statistical characteristics. Furthermore, the conflicting problem of robustness and imperceptibility is effectively resolved by the DE optimization. Simulation results demonstrate that both the LWT-DCT-SVD and DWT-DCT-SVD methods not only have good imperceptibility performance, but also resist general signal processing, hybrid and desynchronization attacks. Compared with the previous DWT-DCT, support vector regression (SVR)-DWT-DCT and DWT-SVD methods, our method obtains more robustness against the selected attacks.
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来源期刊
IEEE Transactions on Audio Speech and Language Processing
IEEE Transactions on Audio Speech and Language Processing 工程技术-工程:电子与电气
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审稿时长
24.0 months
期刊介绍: The IEEE Transactions on Audio, Speech and Language Processing covers the sciences, technologies and applications relating to the analysis, coding, enhancement, recognition and synthesis of audio, music, speech and language. In particular, audio processing also covers auditory modeling, acoustic modeling and source separation. Speech processing also covers speech production and perception, adaptation, lexical modeling and speaker recognition. Language processing also covers spoken language understanding, translation, summarization, mining, general language modeling, as well as spoken dialog systems.
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