Lattice-Based Minimum-Distortion Data Hiding
This work addresses the need for low-distortion data hiding in sensitive domains such as medical or physiological signals, though it is incremental as it builds upon the established QIM scheme.
The paper tackles the problem of minimizing distortion in data hiding for applications like medical signals by proposing MD-QIM, a modified version of QIM that moves data points only to lattice region boundaries, resulting in significantly lower MSE, higher PSNR, and reduced PRD compared to QIM.
Lattices have been conceived as a powerful tool for data hiding. While conventional studies and applications focus on achieving the optimal robustness versus distortion tradeoff, in some applications such as data hiding in medical/physiological signals, the primary concern is to achieve a minimum amount of distortion to the cover signal. In this paper, we revisit the celebrated quantization index modulation (QIM) scheme and propose a minimum-distortion version of it, referred to as MD-QIM. The crux of MD-QIM is to move the data point to only the boundary of the Voronoi region of the lattice point indexed by a message, which suffices for subsequent correct decoding. At any fixed code rate, the scheme achieves the minimum amount of distortion by sacrificing the robustness to the additive white Gaussian noise (AWGN) attacks. Simulation results confirm that our scheme significantly outperforms QIM in terms of mean square error (MSE), peak signal to noise ratio (PSNR) and percentage residual difference (PRD).