Robust watermark extraction using SVD-based dynamic stochastic resonance

In this paper, a novel dynamic stochastic resonance (DSR)-based non-blind watermark extraction technique has been proposed for robust extraction of a grayscale watermark. The watermark embedding has been carried out using singular value decomposition (SVD). Dynamic stochastic resonance has been strategically used to improve the robustness of the extraction algorithm by utilizing the noise added during attacks itself. Resilience of this technique to attacks has been tested in the presence of various noise, geometrical, enhancement, compression and filtering attacks. Using the DSR-based proposed extraction algorithm, a very robust extraction of watermark can be done without trading-off with visual quality of the watermarked image. Performance of the proposed technique has also been compared with the plain SVD-based and hybrid DCT-SVD based technique and is found to give better performance.