Dynamic stochastic resonance-based improved watermark extraction in DWT-SVD domain

In this paper, a Dynamic Stochastic Resonance (DSR)-based robust watermark extraction technique has been presented in combined DWT-SVD domain. The singular values of grayscale watermark image have been embedded in the singular values of the approximation sub-band of audio signal, obtained after DWT decomposition. DSR has been used in the extraction process to improve the authenticity of the extracted watermark by utilizing the noise or degradation introduced during different signal processing attacks. DSR is an iterative process that tunes the coefficients of a possibly attacked watermarked audio signal so that effect of noise is suppressed and hidden information is enhanced. An adaptive optimization procedure has been adopted for selection of bistable parameters to achieve maximum correlation coefficient between original and extracted watermark to ensure minimum computational complexity. Resilience of this technique has been tested in presence of various signal processing attacks like amplification, zero-cross, exchange, smooth, stat, add dynamic noise and cut-sample. Using the proposed technique, a robust extraction of watermark is achieved without trading-off the audibility of audio signal. Comparison with plain DWT-SVD-based technique suggests that the proposed DSR-based audio watermarking scheme gives remarkably better performance in terms of correlation between original and extracted watermarks.