基于JPEG双量化效应的图像盲取证

JPEG图像的双量化效应为JPEG图像的篡改检测提供了重要线索.根据JPEG图像被局部篡改后,又被保存为JPEG格式时,未被篡改的区域(背景区域)的离散余弦变换(DCT)系数会经历双重JPEG压缩,篡改区域的DCT系数则只经历了1次JPEG压缩.而JPEG图像在经过离散余弦变换后其DCT域的交流(AC)系数的分布符合一个用合适的参数来描述的拉普拉斯分布,在此基础上提出了一种JPEG图像重压缩概率模型来描述重压缩前后DCT系数统计特性的变化,并依据贝叶斯准则,利用后验概率表示出图像篡改中存在的双重压缩效应块和只经历单次压缩块的特征值.然后设定阈值,通过阈值进行分类判断就可以实现对篡改区域的自动检测和提取.实验结果表明,该方法能快速并准确地实现篡改区域的自动检测和提取,并且在第2次压缩因子小于第1次压缩因子时,检测结果相对于利用JPEG块效应不一致的图像篡改盲检测算法和利用JPEG图像量化表的图像篡改盲检测算法有了明显的提高.

Blind image forensics based on JPEG double quantization effect

The double quantization effect of JPEG (Joint Photographic Experts Group) provides important clues for detecting image tampering. When an original JPEG image undergoes localized tampering and is saved again in JPEG format, the Discrete Consine Transform (DCT) coefficients of untampered regions would undergo double JPEG compressing, while the DCT coefficients of tampered regions would only undergo a single compression. The Alternating Current (AC) coefficient distribution accords with a Laplace probability density distribution described with a suitable parameter. And on this basis, this paper proposed a new double compression probability model of JPEG image to describe the change of DCT coefficients after the double compression, and combined the Bayes criterion to express the eigenvalues of the image blocks which have undergone the single and double JPEG compression. A threshold was set for the eigenvalues. Then the tampered region was automatically detected and extracted by using the threshold to classify the eigenvalues. The experimental results show that the method can detect and locate the tamped area effectively and it outperforms in terms of the detection result compared with the blind detection algorithm of composite images by measuring inconsistencies of JPEG blocking artifact and image forgery detection algorithm based on quantization table especially when the second compression factor is smaller than the first one.