Robust detection of median filtering based on combined features of difference image

Median filtering is a widely used method for denoising and smoothing regions of an image; it has drawn much attention from researchers of image forensic. A new detection scheme of median filtering based on combined features of difference image (CFDI) is proposed in this paper. In the proposed scheme, the combined features consist of joint conditional probability density functions (JCPDFs) of first-order and second-order difference image (DI), the principal component analysis (PCA) is used to reduce the dimensionality of JCPDFs, and thus, the final features are obtained for the given threshold. A large number of experiments on single database and compound databases show that, the proposed scheme achieves superior performance on the uncompressed image datasets, and it also achieves better performance compared with state-of-the-art methods, especially for strong JPEG compression and low resolution images.