A feature dimension reduction means based on affine clustering was worked out to solve the problem of the features of rich model’s high-dimension and dimension disaster led by much redundancy.This method analyzed the structure of rich model and defined sub model feature distance with nonlinear distance definition,using the affine clustering algorithm and the image spectrum theory to determine the clustering center of features.The sub model feature which has a high occurrence probability in the clustering center was considered as the optimal clustering center,and conducted steganalysis by Fisher ensemble classifier.The experiment showed that the testing error rate EOOB can be decreased by 1%～2% compared to original feature for the steganalysis of S-UNIWARD,WOW,HUGO stegography by the dimension reduction means when the dimensionality of SRM (spatial rich model) is down to 5 525.Therefore,the method in this paper will fulfill the improvement in feature dimension reduction and the effect of steganalysis.
