A statistical model for quantized AC block DCT coefficients in JPEG compression and its application to detecting potential compression history in bitmap images

Gopal Narayanan, Yun Qing Shi

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

3 Scopus citations

Abstract

We first develop a probability mass function (PMF) for quantized block discrete cosine transform (DCT) coefficients in JPEG compression using statistical analysis of quantization, with a Generalized Gaussian model being considered as the PDF for non-quantized block DCT coefficients. We subsequently propose a novel method to detect potential JPEG compression history in bitmap images using the PMF that has been developed. We show that this method outperforms a classical approach to compression history detection in terms of effectiveness. We also show that it detects history with both independent JPEG group (IJG) and custom quantization tables.

Original languageEnglish (US)
Title of host publicationDigital Watermarking - 9th International Workshop, IWDW 2010, Revised Selected Papers
PublisherSpringer Verlag
Pages75-89
Number of pages15
ISBN (Print)9783642184048
DOIs
StatePublished - 2011

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6526 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • General Computer Science

Keywords

  • Compression History
  • Generalized Gaussian
  • Image Forensics
  • JPEG
  • PMF

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