Rational dither modulation watermarking using a perceptual model

Quantization index modulation (QIM) is a computationally efficient method of informed watermarking. However, the original method is particularly sensitive to variations in the amplitude of the signal. Previously, we proposed using a modification of Watson's perceptual model to adaptively adjust the quantization index step size. This simultaneously improved both the robustness and fidelity of the watermarked image and, most importantly, provided invariance (to a large degree) to valumetric scaling. Contemporaneously, rational dither modulation was proposed as an alternative QIM with valumetric invariance. In this paper, we combine the two methods and compare the performance of the new algorithm with our previous results. Experimental results demonstrate that the new algorithm outperforms the previous algorithms over the entire range of valumetric scale factors, albeit at the expense of a small decrease in fidelity. However all algorithms have a superior performance and improved fidelity compared with QIM

[1]  Fernando Pérez-González,et al.  Rational dither modulation: a novel data-hiding method robust to value-metric scaling attacks , 2004, IEEE 6th Workshop on Multimedia Signal Processing, 2004..

[2]  Qiao Li,et al.  Using perceptual models to improve fidelity and provide invariance to valumetric scaling for quantization index modulation watermarking , 2005, Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005..

[3]  Ingemar J. Cox,et al.  Digital Watermarking , 2003, Lecture Notes in Computer Science.

[4]  J. Chou,et al.  On the duality between distributed source coding and data hiding , 1999, Conference Record of the Thirty-Third Asilomar Conference on Signals, Systems, and Computers (Cat. No.CH37020).

[5]  Ton Kalker,et al.  Adaptive quantization watermarking , 2004, IS&T/SPIE Electronic Imaging.

[6]  Bernd Girod,et al.  Estimation of amplitude modifications before SCS watermark detection , 2002, IS&T/SPIE Electronic Imaging.

[7]  Max H. M. Costa,et al.  Writing on dirty paper , 1983, IEEE Trans. Inf. Theory.

[8]  Kyung-Ae Moon,et al.  EM Estimation of Scale Factor for Quantization-Based Audio Watermarking , 2003, IWDW.

[9]  Andrew B. Watson,et al.  DCT quantization matrices visually optimized for individual images , 1993, Electronic Imaging.

[10]  G.W. Wornell,et al.  An information-theoretic approach to the design of robust digital watermarking systems , 1999, 1999 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings. ICASSP99 (Cat. No.99CH36258).

[11]  Ingemar J. Cox,et al.  Watermarking as communications with side information , 1999, Proc. IEEE.