Using noise inconsistencies for blind image forensics
Using noise inconsistencies for blind image forensics
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DOI：
10.1016/j.imavis.2009.02.001
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发表时间：
2009-09
期刊：
影响因子：
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通讯作者：
Babak Mahdian;S. Saic
中科院分区：
文献类型：
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作者：
Babak Mahdian;S. Saic
隐藏篡改痕迹的常用工具是向更改的图像区域添加局部随机噪声。噪声退化是许多主动或被动图像伪造检测方法失败的主要原因。通常，噪声量在整个真实图像上是均匀的。添加局部随机噪声可能导致图像噪声的不一致。因此，检测到图像中的各种噪声水平可能意味着篡改。在本文中，我们提出了一种新的方法，能够将一个调查的图像划分成各种分区均匀的噪声水平。换句话说，我们引入了一种检测噪声水平变化的分割方法。我们假设加性白色高斯噪声。几个例子来证明所提出的方法的输出。噪声估计部分的效率作为不同的噪声标准偏差，区域大小和各种JPEG压缩质量的函数的一个广泛的定量措施，以及提出。
A commonly used tool to conceal the traces of tampering is the addition of locally random noise to the altered image regions. The noise degradation is the main cause of failure of many active or passive image forgery detection methods. Typically, the amount of noise is uniform across the entire authentic image. Adding locally random noise may cause inconsistencies in the image’s noise. Therefore, the detection of various noise levels in an image may signify tampering. In this paper, we propose a novel method capable of dividing an investigated image into various partitions with homogenous noise levels. In other words, we introduce a segmentation method detecting changes in noise level. We assume the additive white Gaussian noise. Several examples are shown to demonstrate the proposed method’s output. An extensive quantitative measure of the efficiency of the noise estimation part as a function of different noise standard deviations, region sizes and various JPEG compression qualities is proposed as well.