@inproceedings{5b3048f569ae435ab4d51fae0f855dab,
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 first proposed to improve the performance of Reversible Data Hiding (RDH). The MLR matrix function that indicates the inner correlations 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 fixed parameters predictors through simple arithmetic combination of its surroundings pixel, 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} 2018, Springer Nature Switzerland AG.; 4th International Conference on Cloud Computing and Security, ICCCS 2018 ; Conference date: 08-06-2018 Through 10-06-2018",
year = "2018",
doi = "10.1007/978-3-030-00015-8_12",
language = "English (US)",
isbn = "9783030000141",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "135--146",
editor = "Elisa Bertino and Xingming Sun and Zhaoqing Pan",
booktitle = "Cloud Computing and Security - 4th International Conference, ICCCS 2018, Revised Selected Papers",
address = "Germany",
}