A norm-space, adaptive, and blind audio watermarking algorithm by discrete wavelet transform

In this paper, combining the robustness of vector norm with that of the approximation components after the discrete wavelet transform (DWT), a blind and adaptive audio watermarking algorithm is proposed. In order to improve the robustness and imperceptibility, a binary image encrypted by Arnold transform as watermark is embedded in the vector norm of the segmented approximation components, the count of which depends on the size of the watermark image, after DWT of the original audio signal through quantization index modulation (QIM) with an adaptive quantization step selection scheme. Moreover, a detailed method has been designed to search the suitable quantization step parameters. Experimental results indicate that even though the capacity of the proposed algorithm is high, up to 102.4 bps, this algorithm is still able to maintain good quality of the audio signal and tolerate a wide class of common attacks such as additive white Gaussian noise (AWGN), Gaussian Low-pass filter, Kaiser Low-pass filter, resampling, requantizing, cutting, MP3 compression and echo.

► The watermark bits are embedded in the vector norm for the first time ever. ► The watermark extraction does not require the original audio signal. ► The scheme is based on QIM with the adaptive quantization steps. ► A detailed method is designed to search the suitable quantization step parameters. ► Keeping high capacity, the scheme still gains good imperceptibility and robustness.