Robust image watermarking technique based on quantization noise visibility thresholds

A tremendous amount of digital multimedia data is broadcasted daily over internet. Digital data being very quickly and easily duplicable, intellectual property rights protection techniques, appeared about fifty years ago (see (14) for an extended review). Digital watermarking was born. Since its birth, many watermarking techniques appeared, in all possible transformed spaces. However, an important lack in watermarking literature concerns the human visual systems models. Several Human Visual System (HVS) model based watermarking techniques have been designed in the late 1990’s. Due to the weak robustness results, especially concerning geometrical distortions, the interest in such studies have been reduced. In this paper, we intend to take benefit from the last advances in HVS models and watermarking techniques to revisit this issue. We hereby demonstrate that it is possible to resist to many attacks, including geometrical distortions, in HVS based watermarking algorithms. The used perceptual model takes into account very advanced features of the HVS , fully identified from psychophysics experiments conducted in our lab. This model have been successfully applied in quality assessment or image coding schemes. In this paper, the human visual system model is used to create a perceptual mask, in order to optimize the watermark’s strength. The obtained optimal watermark ensures both invisibility and robustness requirements. Contrary to most watermarking schemes using advanced perceptual masks, in order to best thwart the de-synchronization problem induced by geometrical distortions, we propose here a Fourier domain embedding and detection technique optimizing the watermark’s amplitude. Finally, the obtained scheme’s robustness is assessed against all attacks provided by the Stirmark benchmark. This work proposes a new digital rights managment technique using an advanced human visual system model and able to resist to various kind of attacks including many geometrical distortions.