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Reversible Data Hiding in Encrypted Images Based on Adaptive Prediction-error Label Map

Yu Ren1, Jiaohua Qin1,*, Yun Tan1, Neal N. Xiong2

1 College of Computer Science and Information Technology, Central South University of Forestry and Technology, Changsha, 410004, China
2 Department of Mathematics and Computer Science, Northeastern State University, OK, 74464, USA

* Corresponding Author: Jiaohua Qin. Email:

Intelligent Automation & Soft Computing 2022, 33(3), 1439-1453.


In the field of reversible data hiding in encrypted images (RDH-EI), predict an image effectively and embed a message into the image with lower distortion are two crucial aspects. However, due to the linear regression prediction being sensitive to outliers, it is a challenge to improve the accuracy of predictions. To address this problem, this paper proposes an RDH-EI scheme based on adaptive prediction-error label map. In the prediction stage, an adaptive threshold estimation algorithm based on local complexity is proposed. Then, the pixels selection method based on gradient of image is designed to train the parameters of the prediction model. In the embedding stage, reserve enough space to embed auxiliary information and secret data embedding by flipping the least significant bits (LSBs) to encrypt the original image. In the receiver, based on the prediction-error map, error-free image recovery can be achieved. Extensive experimental results have shown that the proposed method can achieve effective pixel prediction results and get a higher embedding rate (ER).


Cite This Article

Y. Ren, J. Qin, Y. Tan and N. N. Xiong, "Reversible data hiding in encrypted images based on adaptive prediction-error label map," Intelligent Automation & Soft Computing, vol. 33, no.3, pp. 1439–1453, 2022.

This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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