A novel difference expansion transform for reversible data embedding

Hyoung Joong Kim, Vasiliy Sachnev, Yun Qing Shi, Jeho Nam, Hyon Gon Choo

Research output: Contribution to journalArticlepeer-review

333 Scopus citations


Reversible data embedding theory has marked a new epoch for data hiding and information security. Being reversible, the original data and the embedded data should be completely restored. Difference expansion transform is a remarkable breakthrough in reversible data-hiding schemes. The difference expansion method achieves high embedding capacity and keeps distortion low. This paper shows that the difference expansion method with the simplified location map and new expandability can achieve more embedding capacity while keeping the distortion at the same level as the original expansion method. Performance of the proposed scheme in this paper is shown to be better than the original difference expansion scheme by Tian and its improved version by Kamstra and Heijmans. This improvement can be possible by exploiting the quasi-Laplace distribution of the difference values.

Original languageEnglish (US)
Article number4539274
Pages (from-to)456-465
Number of pages10
JournalIEEE Transactions on Information Forensics and Security
Issue number3
StatePublished - Sep 2008

All Science Journal Classification (ASJC) codes

  • Safety, Risk, Reliability and Quality
  • Computer Networks and Communications


  • Data hiding
  • Information security
  • Multimedia systems
  • Reversible data embedding
  • Reversible integer transform


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