This study presents a high-performance audio watermarking scheme using spread spectrum modulation. Unlike conventional extractors which use simple correlation, this watermarking scheme exploits the perceptual characteristic of the watermarked audio before correlation. It is noted that although the watermark extractor works blindly neither which the original audio signal nor the embedded watermark signal is available, however, the spectral power structure of embedded watermark can be estimated using perceptual analysis methods. With this information, the watermark performance is improved by introducing an estimation-equalisation-correlation based extraction mechanism. The preequaliser at the extractor is carefully designed to obtain optimised extraction performance. Moreover, the perceptual analysis and shaping method are improved to make sure the watermark estimation is accurate. The perceptual characteristic aware extraction-based watermarking scheme achieves high embedding capacity up to 43 bps/channels, with low perceptual distortion to the host audio. Experiments on real audio signals show that the proposed watermarking scheme achieves high performance and is robust against various types of attacks.

This paper addresses the audio piracy problem over Internet by tweaking data redundancy of host media signal for optimized embedding and extraction of spread spectrum watermarking. In particular, we take into account a special feature that host audio signals have the short‐time stationary property and their major power can be removed using linear prediction filter. By combining the redundancy removing and the improved spread spectrum modulation, host interference is canceled with minimized embedding distortion to the host audio. The data redundancy removing is also applied at the receiver to achieve matched filtering and improved performance. Experiments based on real audio signals show that our proposed scheme performs robustly against various kinds of channel attacks while maintaining high extraction performance. Copyright © 2016 John Wiley & Sons, Ltd.

No abstract