Reversible Watermarking based on Invariant Image Classification and Dynamical Error Histogram Shifting

In this article, we present a novel reversible watermarking scheme. Its originality stands in identifying parts of the image that can be watermarked additively with the most adapted lossless modulation between: Pixel Histogram Shifting (PHS) or Dynamical Error Histogram Shifting (DEHS). This classification process makes use of a reference image derived from the image itself, a prediction of it, which has the property to be invariant to the watermark addition. In that way, watermark embedded and reader remain synchronized through this image of reference. DEHS is also an original contribution of this work. It shifts predict-errors between the image and its reference image taking care of the local specificities of the image, thus dynamically. Conducted experiments, on different medical image test sets issued from different modalities and some natural images, show that our method can insert more data with lower distortion than the most recent and efficient methods of the literature.