A High Capacity Reversible Watermarking Algorithm Based on Block-Level Prediction Error Histogram Shifting
Xin Lai Tang, Linna Zhou, Dan Liu, Yi Zhang · 2020
The paper proposes a high capacity reversible watermarking algorithm based on block-level prediction error histogram shifting. This algorithm, in contrast to the known prediction error histogram shifting based ones, provides a higher embedding capacity, which is achieved by employing similarity among adjacent blocks rather than simply pixels inside of a block. The imperceptibility is ensured by the premise that once the block selected is small enough, the center pixels of adjacent blocks have high probability of similarity or equality. At last, the effectiveness and performance are evaluated by experiments and the result shows that our proposed algorithm has higher capacity under the same imperceptibility compared with the classic prediction error histogram shifting based reversible watermarking algorithm as well as the state-of-the-art.