Statistical modelling and steganalysis of DFT-based image steganography

Ying Wang, Pierre Moulin

Research output: Chapter in Book/Report/Conference proceedingConference contribution


An accurate statistical model of cover images is essential to the success of both steganography and steganalysis. We study the statistics of the full-frame two-dimensional discrete Fourier transform (DFT) coefficients of natural images and show that the independently and identically distributed model with unit exponential distribution is not a sufficiently accurate description of the statistics of normalized image periodograms. Consequently, the stochastic quantization index modulation (QIM) algorithm that aims at preserving this model is detectable in principle. To discriminate the resulted stegoimages from cover images, we train a learning system on them. Building upon a state-of-the-art steganalysis method using the statistical moments of wavelet characteristic functions, we propose new features that are more sensitive to data embedding. The addition of these features significantly improves the steganalyzer's receiver operating characteristic (ROC) curve.

Original languageEnglish (US)
Title of host publicationSecurity, Steganography, and Watermarking of Multimedia Contents VIII - Proceedings of SPIE-IS and T Electronic Imaging
StatePublished - 2006
EventSecurity, Steganography, and Watermarking of Multimedia Contents VIII - San Jose, CA, United States
Duration: Jan 16 2006Jan 19 2006

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
ISSN (Print)0277-786X


OtherSecurity, Steganography, and Watermarking of Multimedia Contents VIII
Country/TerritoryUnited States
CitySan Jose, CA


  • Full-frame DFT
  • Machine learning
  • Statistical modelling
  • Steganalysis
  • Steganography
  • Stochastic QIM

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering


Dive into the research topics of 'Statistical modelling and steganalysis of DFT-based image steganography'. Together they form a unique fingerprint.

Cite this