Universal Image Steganalysis Based on Wavelet Packet Decomposition and Empirical Transition Matrix in Wavelet Domain

In the paper, a new universal image steganalysis system based on wavelet packet decomposition (WPD) and empirical transition matrix in wavelet domain is proposed. First, it decomposes the test image using two-level Haar WPD. The statistical analysis is made both for the test image and their wavelet packet subbands. Second, it exploits the interscale and intrascale dependencies between wavelet coefficients. Markov empirical transition matrices are used to capture these dependencies. Fisher linear discriminator (FLD) is applied as classifier to distinguish between cover images and stego images. The experimental results have demonstrated that the proposed scheme has outperformed the existing steganalyzers in attacking a wide range of steganographic schemes include SSIS (spread spectrum image steganography), Hide4PGP, Jsteg, F5, OutGuess.