Spread Transform Dither Modulation using a Perceptual Model

In previous work, we demonstrated how perceptual modeling can be applied to dither modulated quantization index modulation and rational dither modulation, to improve both robustness and fidelity. These algorithms were shown to be significantly more robust to valumetric scaling. However, they, and their predecessors, remain extremely sensitive to re-quantization which commonly occurs due to JPEG compression, numerical rounding and analog-to-digital conversion. It is well known that spread transform dither modulation (STDM) is more robust to re-quantization. In this paper we describe how to incorporate a perceptual model into this framework and present two algorithms based on Watson´s perceptual model. Experimental results of robustness to JPEG compression are reported for 1000 images at embedding rates of 1/32 and 1/320. At the high embedding rate, the robustness of the two algorithms is the same as STDM but the perceptual distortion is reduced 23 to about 4, based on Watson´s perceptual distance. At the lower embedding rate, we simultaneously observed superior robustness to STDM as well as improved fidelity. If the perceptual distance rather than the document-to-watermark ratio (DWR) is held fixed, then the two adaptive spread transform methods exhibit significant improvements in robustness to JPEG compression