• Title/Summary/Keyword: Piecewise auto-regression

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Reversible Data Hiding Using a Piecewise Autoregressive Predictor Based on Two-stage Embedding

  • Lee, Byeong Yong;Hwang, Hee Joon;Kim, Hyoung Joong
    • Journal of Electrical Engineering and Technology
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    • v.11 no.4
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    • pp.974-986
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    • 2016
  • Reversible image watermarking, a type of digital data hiding, is capable of recovering the original image and extracting the hidden message with precision. A number of reversible algorithms have been proposed to achieve a high embedding capacity and a low distortion. While numerous algorithms for the achievement of a favorable performance regarding a small embedding capacity exist, the main goal of this paper is the achievement of a more favorable performance regarding a larger embedding capacity and a lower distortion. This paper therefore proposes a reversible data hiding algorithm for which a novel piecewise 2D auto-regression (P2AR) predictor that is based on a rhombus-embedding scheme is used. In addition, a minimum description length (MDL) approach is applied to remove the outlier pixels from a training set so that the effect of a multiple linear regression can be maximized. The experiment results demonstrate that the performance of the proposed method is superior to those of previous methods.