Image Watermarking Robust Against Non-Linear Value-Metric Scaling Based on Higher Order Statistics

A new QIM-based image watermarking system for still im- ages is proposed. The new system is expressly designed to cope with non-linear value-metric scaling attacks such as his- togram stretching and gamma correction. By recognizing that any value-metric scaling attack must not change the global ap- pearance of the image, we argue that the watermark should be inserted into high level visual features. We move a first step into this direction by proposing a system embedding the wa- termark into the kurtosis of selected image blocks. Though the kurtosis is not strictly invariant against non-linear gain, its value tends to remain constant whenever the image content is not altered significantly. The experiments we carried out con- firm the validity of the new system, though some problems still need to be solved to make it suitable for real applications.