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

A new QIM-based image watermarking system for still images is proposed. The new system is expressly designed to cope with non-linear value-metric scaling attacks such as histogram stretching and gamma correction. By recognizing that any value-metric scaling attack must not change the global appearance 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 watermark 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 confirm the validity of the new system, though some problems still need to be solved to make it suitable for real applications