Reversible Data Hiding Based on Blockwise Prediction with Quadtree Concepts

Reversible data hiding is famous for the reversibility in information security researches. For assessing the effectiveness of reversible data hiding schemes, the marked image quality and the payload should be compared, and the reversibility should be guaranteed. It would be advantageous to take the inherent characteristics of original image into consideration to enhance the image quality and embedding payload. By generating predicted image and taking the differences between predicted and original image, a much enhanced amount of payload can be achieved. We employ quadtree decomposition for presenting image characteristics, choose different sets of prediction parameters, and perform embedding with reversible data hiding. Experimental results have provided the flexibility for performance enhancements.