Multi-directional and multi-scale perturbation approaches for blind forensic median filtering detection

The forensic detection of median filtering has recently attracted the attention of the research community, mainly because of the median filtering potential uses for tampering and concealing image tampering traces in digital images. In this paper, we propose multi-scale and multi-perturbation solutions that build a highly discriminative feature space, which highlights the artifacts of median filtering by means of image quality measures. The proposed methods achieve promising results when validated with a series of real-world test cases, comprising different image compression levels, resolutions, and also a cross-dataset validation protocol.