Steganalysis of color images weaken or ignore the correlation among different color channels by only using single signal channel. The noise model of stego color images is analyzed, and a general steganalysis algorithm based on noise model and color channels integration is proposed. Firstly, the wavelet decomposition of the image is made, and a filtering operation is applied to obtain the wavelet subbands of noise image. Secondly, noise gradient orientation sequences between any two noise channels and noise gradient sum sequence are extracted from the noise wavelet subbands. Thirdly, color gradient orientation sequences between any two channels and color gradient sum sequence are extracted from the color image. Finally, the Hilbert-Huang transform based vibration features of these sequences are integrated as eigenvectors, and SVM is used to detect images. The experimental results show that the proposed technique realizes the reliable steganalysis of color images with higher correct rate and lower false positive rate, compared with traditional color image steganalysis algorithms.%彩色图像的隐写分析大多在单信号通道进行,弱化或忽略了彩色图像不同颜色通道的相关性.通过分析彩色图像隐写噪声模型,提出了基于噪声模型和通道融合的通用彩色图像隐写分析算法,算法基于小波滤波,得到待检测图像的噪声小波系数子带,从该类子带中提取刻画噪声通道融合特征的噪声梯度方向序列及噪声梯度和序列,结合描述彩色图像颜色通道融合特征的颜色梯度方向序列及颜色梯度和序列,应用HHT变换提取各序列的振荡特征,构建基于Hilbert谱的特征向量,应用SVM分类器进行分类判别.实验表明,与已有的彩色图像隐写分析算法比较,所提出的算法误检率低,具有更好的检测效果.
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