An Improved Reversible Data Hiding in Encrypted Images using Parametric Binary Tree Labeling
This work addresses the need for secure and efficient data embedding in encrypted images, with potential applications in privacy-preserving communication, but it appears incremental as it builds on existing reversible data hiding techniques.
The paper tackles the problem of reversible data hiding in encrypted images by proposing an improved scheme that uses parametric binary tree labeling to exploit spatial correlation across the entire image, achieving higher embedding rates compared to state-of-the-art methods.
This work proposes an improved reversible data hiding scheme in encrypted images using parametric binary tree labeling(IPBTL-RDHEI), which takes advantage of the spatial correlation in the entire original image but not in small image blocks to reserve room for hiding data. Then the original image is encrypted with an encryption key and the parametric binary tree is used to label encrypted pixels into two different categories. Finally, one of the two categories of encrypted pixels can embed secret information by bit replacement. According to the experimental results, compared with several state-of-the-art methods, the proposed IPBTL-RDHEI method achieves higher embedding rate and outperforms the competitors. Due to the reversibility of IPBTL-RDHEI, the original plaintext image and the secret information can be restored and extracted losslessly and separately.