IEEE Access (Jan 2022)

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

  • Yuan-Yu Tsai,
  • Hong-Lin Liu,
  • Pei-Lin Kuo,
  • Chi-Shiang Chan

DOI
https://doi.org/10.1109/ACCESS.2022.3171578
Journal volume & issue
Vol. 10
pp. 49347 – 49358

Abstract

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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.

Keywords