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A Multiple Linear Regression Based High-Performance Error Prediction Method for Reversible Data Hiding

  • Bin MaEmail author
  • Xiaoyu Wang
  • Bing Li
  • Yunqing Shi
Conference paper
Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST, volume 255)

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

Multiple linear regression Reversible data hiding Prediction error Embedded capacity 

References

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Copyright information

© ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2018

Authors and Affiliations

  1. 1.School of Information ScienceQilu University of Technology (Shandong Academic of Science)JinanChina
  2. 2.New Jersey Institute of TechnologyNew JerseyUSA

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