Anti-Forensics of Lossy Predictive Image Compression
Li Y.; Zhou J.
2015-12-01
Source PublicationIEEE Signal Processing Letters
ISSN10709908
Volume22Issue:12Pages:2219-2223
Abstract

Image compression evidence has been utilized as an important forensic feature to justify image authenticity. However, some recent studies showed that the compression evidence of block transform-based image coding, e.g., JPEG and JPEG2000, can be effectively erased by adding designed dither noise in the transform domain. In this paper, we demonstrate that it is also feasible to hide the compression evidence of lossy predictive image coding, a class of compression paradigm widely employed in critical scenarios. To tackle the challenging issue of error propagation inherent to predictive coding, we design a prediction-direction preserving strategy, allowing us to add dither noise in the prediction error (PE) domain, while minimizing the incurred distortion. Extensive experimental results are provided to verify the effectiveness of the proposed anti-forensic algorithm for lossy predictive image coding.

KeywordAnti-forensics Lossy Predictive Image Coding
DOI10.1109/LSP.2015.2472561
URLView the original
Indexed BySCI
Language英语
WOS Research AreaEngineering
WOS SubjectEngineering, Electrical & Electronic
WOS IDWOS:000360833300002
Fulltext Access
Citation statistics
Cited Times [WOS]:5   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
CollectionDEPARTMENT OF COMPUTER AND INFORMATION SCIENCE
AffiliationUniversidade de Macau
Recommended Citation
GB/T 7714
Li Y.,Zhou J.. Anti-Forensics of Lossy Predictive Image Compression[J]. IEEE Signal Processing Letters,2015,22(12):2219-2223.
APA Li Y.,&Zhou J..(2015).Anti-Forensics of Lossy Predictive Image Compression.IEEE Signal Processing Letters,22(12),2219-2223.
MLA Li Y.,et al."Anti-Forensics of Lossy Predictive Image Compression".IEEE Signal Processing Letters 22.12(2015):2219-2223.
Files in This Item:
There are no files associated with this item.
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Li Y.]'s Articles
[Zhou J.]'s Articles
Baidu academic
Similar articles in Baidu academic
[Li Y.]'s Articles
[Zhou J.]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Li Y.]'s Articles
[Zhou J.]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.