Reversible data hiding using a piecewise autoregressive predictor based on two-stage embedding

Byeong Yong Lee, Hee Joon Hwang, Hyong Joong Kim

Research output: Contribution to journalArticle

8 Citations (Scopus)

Abstract

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.

Original languageEnglish
Pages (from-to)974-986
Number of pages13
JournalJournal of Electrical Engineering and Technology
Volume11
Issue number4
DOIs
Publication statusPublished - 2016 Jul 1

Keywords

  • Context prediction
  • Least-squared-based method
  • Minimum description length
  • Piecewise auto-regression
  • Prediction-error expansion
  • Reversible data hiding

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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