A Random Matrix Approach to the Forensic Analysis of Upscaled Images

@article{Vx00E1zquezPadx00EDn2017ARM,
  title={A Random Matrix Approach to the Forensic Analysis of Upscaled Images},
  author={David Vx00E1zquez-Padx00EDn and Fernando Px00E9rez-Gonzx00E1lez and Pedro Comesax00F1a-Alfaro},
  journal={IEEE Transactions on Information Forensics and Security},
  year={2017},
  volume={12},
  pages={2115-2130}
}
The forensic analysis of resampling traces in upscaled images is addressed via subspace decomposition and random matrix theory principles. In this context, we derive the asymptotic eigenvalue distribution of sample autocorrelation matrices corresponding to genuine and upscaled images. To achieve this, we model genuine images as an autoregressive random field and we characterize upscaled images as a noisy version of a lower dimensional signal. Following the intuition behind Marčenko-Pastur law… CONTINUE READING

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