基于后验概率和滤色阵列特性的图像篡改检测算法

Abstract

针对图像采集过程中插值算法对图像三原色之间所引入的插值特性，论文提出一种基于后验概率和滤色阵列特性的图像篡改检测算法。首先提取待测图像绿色通道分量，引入二维预测滤波构建预测误差函数；然后分块提取特征，分析原始与篡改图像所提特征的直方图特性，从而建立特征的高斯混合统计模型，并借助EM算法估计模型参数；计算子块特征作为原始块的后验概率，定义似然率并应用到每个子块中，从而可得到篡改区域映射图，完成本次检测。仿真结果表明，该算法具有较强的鲁棒性，能够对图像篡改区域进行较准确地定位。 Focused on the artifacts between the three primaries of an image introduced by the interpolation algorithm during its acquisition process, an image tampering detection algorithm based on the posterior probability and the color filter array artifacts is proposed. Firstly, the green channel component of the image is extracted, and the two-dimensional predictive filter is used to construct the predictive error function. Then the histograms’ character of original and tampering images is analyzed, and then the Gaussian mixture statistical model is established. EM algorithm is applied to estimate the model parameters. Then the posterior probability of each sub-block as an original block is calculated, and the feature likelihood is defined and it is applied to every sub-block, so that the tampering-area map can be obtained to complete the detection. The simulation results show that the algorithm has strong robustness and can locate the image’s tampered region more accurately.