Audio Watermarking Based on LWT and SD

Abstract

Chapter 5 proposes an audio watermarking method based on LWT and Schur decomposition (SD). To the best of our knowledge, this is the first audio watermarking method based on LWT, SD, and quantization jointly. Initially, the watermark data are preprocessed to enhance the confidentiality of the proposed method. Then, the original audio is segmented into nonoverlapping frames and LWT is applied to each frame. SD is applied to the selected low-frequency LWT coefficients represented in a matrix form. Watermark data are embedded into the largest element of the upper triangular matrix obtained from the selected LWT coefficients of each frame. Experimental results confirm that the embedded data are highly robust against various attacks. Moreover, it shows superior performance than the state-of-the-art watermarking methods reported recently. In this chapter, an audio watermarking method in lifting wavelet transform (LWT) domain based on Schur decomposition (SD) is introduced. The main features of the proposed method are: (i) it utilizes the LWT and SD jointly, (ii) it uses Gaussian map, containing the chaotic characteristic to enhance the confidentiality of the proposed scheme, (iii) watermark extraction process is blind, (iv) subjective and objective evaluations reveal that the proposed scheme maintains high audio quality, and (v) it achieves a good trade-off among imperceptibility, robustness, and data payload. Experimental results indicate that the proposed watermarking scheme is highly robust against various attacks such as noise addition, cropping, re-sampling, re-quantization, and MP3 compression. Moreover, it outperforms state-of-the-art methods [9–10, 14–16, 20, 23–24, 26] in terms of imperceptibility, robustness, and data payload. The data payload of the proposed scheme is 172.39 bps, which is relatively higher than that of the state-of-the-art methods.