Reversible Data Hiding Scheme Based on VQ Prediction and Adaptive Parametric Binary Tree Labeling for Encrypted Images

In this paper, we propose a reversible data hiding scheme for the encrypted images (RDHEI) based on vector quantization (VQ) prediction and parametric binary tree labeling (PBTL). VQ compression is lossy image method, difference between original decompressed small when length of codebook sufficient. Thus, can be applied as tool pixel value prediction. Based prediction, PBTL method to label embeddable non-embeddable pixels. Through adaptive setting parameters, modified provide optimal strategies thus maximize overall embedding capacity. Furthermore, index secret are stream ciphered avoid leakage content information. Different metrics used show that marked highly secure. comparison with several state-of-the-art schemes, our outperforms related works in rate two commonly databases. addition, extraction recovery operated separately according authorization.