Double linear regression prediction based reversible data hiding in encrypted images

• Published in: Multimedia tools and applications Vol. 80; no. 2; pp. 2141 - 2159
• Main Authors: Li, Fengyong, Zhu, Hengjie, Yu, Jiang, Qin, Chuan
• Format: Journal Article
• Language: English
• Published: New York Springer US 2021; Springer Nature B.V
• Subjects: Computer Communication Networks; Computer Science; Data recovery; Data Structures and Information Theory; Embedding; Encryption; Errors; Image quality; Model accuracy; Multimedia Information Systems; Pixels; Prediction models; Predictions; Regression analysis; Regression models; Special Purpose and Application-Based Systems; Image encryption; Reversible data hiding; Double linear regression prediction
• ISSN: 1380-7501; 1573-7721
• DOI: 10.1007/s11042-020-09805-6

Existing prediction-based works on reversible data hiding in encrypted images usually embed the secret messages by referring to the difference between current pixel and its predicted value. An accurate prediction model may promote an improvement of embedding capacity. Existing schemes, however, may not work well due to involving a bad prediction model so that their embedding capacity cannot be improved further. To address the problem, this paper proposes a new reversible data hiding scheme in encrypted images by designing double linear regression prediction model. Proposed model can significantly improve the prediction accuracy of current pixel based on neighboring pixels, more auxiliary rooms are thus vacated to embed secret data. Furthermore, a prediction error map is constructed to mark the error positions caused by inaccurate prediction, which can be further compressed lossless to lower the capacity of auxiliary data. Reversible recovery for original image can be finally achieved successfully. Experimental results demonstrate that the proposed scheme significantly improves prediction accuracy and data embedding capacity by combining double linear regression prediction model and prediction error map, and then can achieve separable and lossless recovery for the original image. Compared with existing works, the proposed scheme can implement a higher visual quality of decrypted images, while maintaining a larger embedding capacity.