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Error-free separable reversible data hiding in encrypted images using linear regression and prediction error map

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Abstract

In this paper, we propose a new reversible data-hiding method in encrypted images. The method is a vacating room after encryption (VRAE) method that attempts to achieve the error-free recovery of images. In previous VRAE methods, errors may occur in recovering images because of inaccurate predictions, so these methods cannot achieve complete reversibility. In addition, these methods have limited embedding rates. To solve these problems, the proposed method uses a linear, regression-based predictor to improve the accuracy of predictions, and it uses a prediction error map to eliminate errors caused by inaccurate predictions. By using the linear regression-based predictor and the prediction error map, the embedding rate of data embedding is improved significantly, and the original image can be recovered with no error. The experimental results showed that the embedding rate of the proposed method can be higher than 0.5 bpp, and the visual quality can be maintained at high embedding rates.

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Acknowledgements

This paper is supported by the Natural Science Foundation of Fujian Province, China (2017 J05104, 2019H0021), the National Natural Science Foundation of China (61701191), and the Xiamen Foundation for Science and Technology (3502Z20173028).

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Authors and Affiliations

  1. Computer Engineering College, Jimei University, Xiamen, 361021, China

    Kaimeng Chen

  2. Department of Information Engineering and Computer Science, Feng Chia University, No. 100 Wenhwa Rd., Seatwen, Taichung, 40724, Taiwan, Republic of China

    Chin-Chen Chang

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  1. Kaimeng Chen
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Chen, K., Chang, CC. Error-free separable reversible data hiding in encrypted images using linear regression and prediction error map. Multimed Tools Appl 78, 31441–31465 (2019). https://doi.org/10.1007/s11042-019-07946-x

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