Adaptive spread-transform dither modulation using an improved luminance-masked threshold

Based on the improved Watson´s model, an adaptive spread-transform dither modulation (ASTDM) algorithm is proposed for efficient watermarking to resist the amplitude scaling and coefficient re-quantization attacks. Firstly, the luminance masking is modified to be consistent with amplitude scaling without affecting the original parameters. Then, by incorporating the improved model with STDM algorithm, a maximum labeling strength and an appropriate quantization step-size shrinking with the local values of a host image are achieved. Experiments demonstrate that with high embedding rate and transparence, ASTDM can greatly increase the robustness against amplitude scaling while retaining anti-re-quantization property, which means the two drawbacks of QIM algorithm are solved simultaneously.