Skip to main navigation Skip to search Skip to main content

Reversible data hiding based on multilevel histogram modification and sequential recovery

  • Zhenfei Zhao
  • , Hao Luo*
  • , Zhe Ming Lu
  • , Jeng Shyang Pan
  • *Corresponding author for this work
  • Sun Yat-Sen University
  • Heilongjiang University of Science and Technology
  • Zhejiang University
  • National Kaohsiung University of Science and Technology

Research output: Contribution to journalArticlepeer-review

Abstract

This paper proposes a reversible data hiding method for natural images. Due to the similarity of neighbor pixels' values, most differences between pairs of adjacent pixels are equal or close to zero. In this work, a histogram is constructed based on these difference statistics. In the data embedding stage, a multilevel histogram modification mechanism is employed. As more peak points are used for secret bits modulation, the hiding capacity is enhanced compared with those conventional methods based on one or two level histogram modification. Moreover, as the differences concentricity around zero is improved, the distortions on the host image introduced by secret content embedding is mitigated. In the data extraction and image recovery stage, the embedding level instead of the peak points and zero points is used. Accordingly the affiliated information is much smaller than in those methods of the kind. A sequential recovery strategy is exploited for each pixel is reconstructed with the aid of its previously recovered neighbor. Experimental results and comparisons with other methods demonstrate our method's effectiveness and superior performance.

Original languageEnglish
Pages (from-to)814-826
Number of pages13
JournalAEU - International Journal of Electronics and Communications
Volume65
Issue number10
DOIs
StatePublished - Oct 2011
Externally publishedYes

Keywords

  • Multilevel histogram modification
  • Reversible data hiding
  • Sequential recovery

Fingerprint

Dive into the research topics of 'Reversible data hiding based on multilevel histogram modification and sequential recovery'. Together they form a unique fingerprint.

Cite this