基于轮廓波变换的隐写分析算法

A contourlet transform-based steganalysis algorithm

基于轮廓波变换对图像表示的优良性质,提出了一种基于轮廓波变换的通用隐写分析算法。综合了轮廓波变换高频子带系数、高频子带噪声残差、高频子带特征函数高阶统计模型,利用支持向量机(support vector ma-chine,SVM)对JSteg、Jphide、F5、Outguess等隐写算法的不同嵌入率进行分类和检测。实验结果表明基于轮廓波变换隐写分析算法对大部分隐写算法具有优良的探测性能。与传统的小波变换相比,轮廓波变换能够更有效地捕捉到图像因密信的嵌入而引起的细微变化。

A universal steganalysis method was proposed by using the superior property of the contourlet transform with representation of an image.It merged the highorder statistics model of coefficient moments statistics,noise residual moments statistics,and characteristic function moments in the high frequency subband of the contourlet domain.At the same time,a nonlinear support vector machine（SVM） classifier was used to classify JSteg,Jphide,F5 and Outguess with different embedding rates.Experimental results showed that the proposed method has the superion discriminative performance for most of steganography methods.Compared with the classical wavelet,the contourlet transform has better detection effect to capture slight differences during embedding messages.