Extending Multi-MSB Prediction and Huffman Coding for Reversible Data Hiding in Encrypted HDR Images

Autor: Yuan-Yu Tsai, Hong-Lin Liu, Pei-Lin Kuo, Chi-Shiang Chan
Jazyk: angličtina
Rok vydání: 2022
Předmět:
Zdroj: IEEE Access, Vol 10, Pp 49347-49358 (2022)
Druh dokumentu: article
ISSN: 2169-3536
DOI: 10.1109/ACCESS.2022.3171578
Popis: Reversible data hiding in encrypted images can simultaneously enhance the image privacy and preserve the message security for the purpose of covert communication and cloud data management. The algorithm extends the multi-MSB prediction and Huffman coding to propose the first reversible data hiding in encrypted HDR images in the Radiance RGBE format. Because of the high similarity among the exponent channel values of neighboring pixels, we directly applied multi-MSB prediction in our proposed preprocessing procedure, yielding considerably increased embedding capacity. We also proposed a novel image encryption method to maintain the characteristics of the images. Subsequently, a distortion-free data hiding algorithm, namely the homogeneity index modification algorithm, was added to further increase embedding capacity. The experimental results demonstrate the feasibility of the proposed algorithm and its ability to increase embedding capacity, embedding rate, and image privacy, support two data hiders, and enable reversibility and separability.
Databáze: Directory of Open Access Journals