How to reconstruct the history of a digital image, and of its alterations

  • Quentin BAMMEY*
  • , Miguel COLOM
  • , Thibaud EHRET
  • , Marina GARDELLA
  • , Rafael GROMPONE
  • , Jean-Michel MOREL
  • , Tina NIKOUKHAH
  • , Denis PERRAUD
  • *Corresponding author for this work

Research output: Book Chapters | Papers in Conference ProceedingsBook ChapterResearchpeer-review

Abstract

This chapter reviews the operations undergone by the raw image and describes the artifacts they leave in the final image. The Internet, digital media, new means of communication and social networks have accelerated the emergence of a connected world where perfect mastery over information becomes utopian. Image manipulation can serve the interests of criminal or terrorist organizations as part of their propaganda. Noise estimation is a necessary preliminary step to most image processing and computer vision algorithms. Noise inconsistency analysis is a rich source for forgery detection due to the fact that forged regions are likely to present different noise models from the rest of the image. Image demosaicing leaves artifacts that can be used to find falsifications. The chapter seeks to determine the compression history of an image. It focuses on the JPEG algorithm, which is nowadays the most common method to store images.
Original languageEnglish
Title of host publicationMultimedia Security 1: Authentication and Data Hiding
EditorsWilliam PUECH
PublisherISTE Group
Pages1-40
Number of pages40
ISBN (Electronic)9781119901808
ISBN (Print)9781789450262
DOIs
Publication statusPublished - 21 Mar 2022
Externally publishedYes

Bibliographical note

Publisher Copyright:
© ISTE Ltd 2022. All rights reserved.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 16 - Peace, Justice and Strong Institutions
    SDG 16 Peace, Justice and Strong Institutions

Keywords

  • Digital media
  • Image demosaicing
  • Image manipulation
  • Image processing
  • JPEG algorithm
  • Noise inconsistency analysis
  • Social networks

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