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Home / Journals / CSSE / Online First / doi:10.32604/csse.2024.038308
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ARTICLE

Multiple Perspective of Multipredictor Mechanism and Multihistogram Modification for High-Fidelity Reversible Data Hiding

Kai Gao1, Chin-Chen Chang1,*, Chia-Chen Lin2,*
1 Department of Information Engineering and Computer Science, Feng Chia University, Taichung, 407, Taiwan
2 Department of Computer Science and Information Engineering, National Chin-Yin University of Technology, Taichung, 411, Taiwan
* Corresponding Authors: Chin-Chen Chang. Email: alan3c@gmail.com; Chia-Chen Lin. Email: ally.cclin@ncut.edu.tw

Computer Systems Science and Engineering https://doi.org/10.32604/csse.2024.038308

Received 07 December 2022; Accepted 24 February 2023; Published online 19 April 2024

Abstract

Reversible data hiding is a confidential communication technique that takes advantage of image file characteristics, which allows us to hide sensitive data in image files. In this paper, we propose a novel high-fidelity reversible data hiding scheme. Based on the advantage of the multipredictor mechanism, we combine two effective prediction schemes to improve prediction accuracy. In addition, the multihistogram technique is utilized to further improve the image quality of the stego image. Moreover, a model of the grouped knapsack problem is used to speed up the search for the suitable embedding bin in each sub-histogram. Experimental results show that the quality of the stego image of our scheme outperforms state-of-the-art schemes in most cases.

Keywords

Data hiding; multipredictor mechanism; high-fidelity; knapsack problem

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