Anti-forensics of Lossy Predictive Image Compression

Jiantao Zhou1, Yuanman Li2

  • 1University of Macau
  • 2University of Macau, Macao

Details

13:30 - 15:30 | Tue 22 Mar | Poster Area G | IFS-P1.5

Session: Multimedia Forensics

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.