@inproceedings{36a379bf3cb0493899729a581bb480fb,
title = "A multiple linear regression based high-performance error prediction method for reversible data hiding",
abstract = "In this paper, a high-performance error-prediction method based on multiple linear regression (MLR) algorithm is proposed to improve the performance of reversible data hiding (RDH). The MLR matrix function indicates the inner correlation between the pixels and its neighbors is established adaptively according to the consistency of pixels in local area of a natural image, and thus the object pixel is predicted accurately with the achieved MLR function that satisfies the consistency of the neighboring pixels. Compared with conventional methods that only predict the object pixel with simple arithmetic combination of its surroundings pixel, the experimental results show that the proposed method can provide a sparser prediction-error image for data embedding, and thus improves the performance of RDH more effectively than those state-of-the-art error prediction algorithms.",
keywords = "Embedded capacity, Multiple linear regression, Prediction error, Reversible data hiding",
author = "Bin Ma and Xiaoyu Wang and Bing Li and Yunqing Shi",
note = "Publisher Copyright: {\textcopyright} ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2018.; 14th International EAI Conference on Security and Privacy in Communication Networks, SecureComm 2018 ; Conference date: 08-08-2018 Through 10-08-2018",
year = "2018",
doi = "10.1007/978-3-030-01704-0_25",
language = "English (US)",
isbn = "9783030017033",
series = "Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST",
publisher = "Springer Verlag",
pages = "441--452",
editor = "Bing Chang and Yingjiu Li and Raheem Beyah and Sencun Zhu",
booktitle = "Security and Privacy in Communication Networks - 14th International Conference, SecureComm 2018, Proceedings",
address = "Germany",
}