A framework for evaluating the data-hiding capacity of image sources

Pierre Moulin, M. Kivanç Mihçak

Research output: Contribution to journalArticle

Abstract

An information-theoretic model for image watermarking and data hiding is presented in this paper. Recent theoretical results are used to characterize the fundamental capacity limits of image watermarking and data-hiding systems. Capacity is determined by the statistical model used for the host image, by the distortion constraints on the data hider and the attacker, and by the information available to the data hider, to the attacker, and to the decoder. We consider autoregressive, block-DCT, and wavelet statistical models for images and compute data-hiding capacity for compressed and uncompressed host-image sources. Closed-form expressions are obtained under sparse-model approximations. Models for geometric attacks and distortion measures that are invariant to such attacks are considered.

Original languageEnglish (US)
Pages (from-to)1029-1042
Number of pages14
JournalIEEE Transactions on Image Processing
Volume11
Issue number9
DOIs
StatePublished - Sep 1 2002

Keywords

  • Autoregressive processes
  • Data hiding
  • Discrete cosine transform
  • Image modeling
  • Image watermarking
  • Information theory
  • Minimax techniques
  • Wavelets

ASJC Scopus subject areas

  • Software
  • Computer Graphics and Computer-Aided Design

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