A Image Steganalysis Method Based on Characteristic Function Moments of Wavelet Subbands and PCA
Li Hui · Xinxi wangluo anquan · 2009
In this paper a universal steganalysis scheme is proposed for images.The scheme is based on the characteristic function moments of three-level wavelet subbands including the further decomposition coefficients of the first scale diagonal subband.The first three statistical moments of are selected to form 51 dimensional features for steganalysis.The same decomposition has been down to the predicted error image,and the first three statistical moments of each band are calculated to form 51 dimensional features.So total 102dimentional features are obtained.Based on K-L conversation,the features are reduced by PCA and the SVM is adopted as the classifier.The simulation results show the proposed scheme has good performance in attacking JHide and Jstego.