Preprocessed and postprocessed quantization index modulation methods for digital watermarking

Quantization index modulation (QIM) methods, a class of digital watermarking and information embedding methods, achieve very efficient trade-offs among the amount of embedded information (rate), the amount of embedding-induced distortion to the host signal, and the robustness to intentional and unintentional attacks. For example, we show that against independent additive Gaussian attacks, which are good models for at least some types of uninformed and unintentional attacks, QIM methods exist that achieve the best possible rate-distortion-robustness trade-offs (i.e., capacity) asymptotically at high rates and achieve performance within a few dB of capacity at ail finite rates. Furthermore, low-complexity realizations of QIM methods, such as so-called dither modulation, have also been shown to achieve favorable rate-distortion-robustness trade-offs. We further develop preprocessing and postprocessing techniques that enable QIM to fully achieve capacity, not only against Gaussian attacks but also against other types of attacks as well. One practical postprocessing technique we develop we refer to as distortion compensation. Distortion compensation has the property that when suitably optimized it is sufficient for use in conjunction with QIM to achieve capacity against Gaussian attacks and against square-error distortion-constrained attacks. More generally, we present the results of a comparative information theoretic analysis of the fundamental performance limits of QIM, distortion-compensated QIM, and other watermarking methods and demonstrate practically achievable gains with experimental results.