Abstract
Detection of multiple JPEG compression of digital images has been attracting more and more interest in the field of multimedia forensics. On the other side, techniques to conceal the traces of multiple compression are being proposed as well. Motivated by a recent trend towards the adoption of universal approaches, we propose a counter-forensic technique that makes multiple compression undetectable for any forensic detector based on the analysis of the histograms of quantized DCT coefficients. Experimental results show the effectiveness of our approach in removing the artifacts of double and also triple compression, while maintaining a good quality of the image.
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Notes
- 1.
Experiments show that using \( \chi ^2\) in place of \( \mathcal {D}\) in this phase lightens the computation without significantly affecting the results.
- 2.
Each contribution may be possibly weighted by some coefficients in order to give more importance to the low frequency coefficients.
- 3.
Performing the rounding for computing \(W_q\) may cause a slight violation of the JND constraint, but it is preferable for the remapping operation.
- 4.
In the transportation problem the objective function of the minimization problem would be the distortion (cost of the transportation), which in our formulation is instead a constraint.
- 5.
This avoids multiple substitutions of the same coefficients.
- 6.
- 7.
The expected histogram is obtained by estimating the histograms of unquantized coefficients (using calibration), then quantizing them according to the quantization factors available in the JPEG header of the file.
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Acknowledgments
This work was partially supported by the European Office of Aerospace Research and Development under Grant FA8655-12-1- 2138: AMULET - A multi-clue approach to image forensics.
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Barni, M., Fontani, M., Tondi, B. (2015). Universal Counterforensics of Multiple Compressed JPEG Images. In: Shi, YQ., Kim, H., Pérez-González, F., Yang, CN. (eds) Digital-Forensics and Watermarking. IWDW 2014. Lecture Notes in Computer Science(), vol 9023. Springer, Cham. https://doi.org/10.1007/978-3-319-19321-2_3
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