Dynamic stochastic resonance-based grayscale logo extraction in hybrid SVD-DCT domain

Abstract

This paper presents a novel dynamic stochastic resonance (DSR)-based technique for robust extraction of a grayscale logo from a tampered watermarked image. The watermark embedding is done on the singular values (SV) of the discrete cosine transform (DCT) coefficients of the cover image. DSR is then strategically applied during the logo extraction process where the SV of DCT coefficients are tuned following a double-well potential model by utilizing the noise introduced during attacks. The resilience of this technique has been tested in the presence of various noises, geometrical distortions, enhancement, compression, filtering and watermarking attacks. The proposed DSR-based technique for logo extraction gives noteworthy robustness without any significant trade-off in perceptual transparency of the watermarked image. A maximization approach has been adopted for the selection of bistable double-well parameters to establish noise-enhanced resonance. When compared with existing watermark extraction techniques based in SVD, DCT, SVD-DCT domains, as well as with their combination with DSR, the results suggest that remarkable improvement of robustness is achieved by using DSR on singular values of DCT.