An Optimal SVD-based Watermarking Framework through Linear Programming

Transparent, robust watermarking schemes tend to insert invisible watermarks with the highest possible energy. Singular values, in singular value decomposition (SVD), are shown to be robust to intentional and unintentional attacks. However, none of the algorithms proposed in the literature considered the visual imperceptibility constraint imposed by the human visual models. In this paper, we introduce an optimal SVD-based embedding framework, based on the well-known linear programming concept. Given a binary sequence of the mark, we show how to insert the message with the highest possible magnitude, without outlawing the just noticeable thresholds driven by the human visual system models in both spatial and linear domains.