Weighted averaging-based sensor pattern noise estimation for source camera identification
Weighted averaging-based sensor pattern noise estimation for source camera identification
复制标题
DOI：
10.1109/icip.2014.7026084
复制
发表时间：
2014-10
期刊：
影响因子：
--
通讯作者：
Ashref Lawgaly;F. Khelifi;A. Bouridane
中科院分区：
文献类型：
--
作者：
Ashref Lawgaly;F. Khelifi;A. Bouridane
传感器图案噪声已广泛应用于图像认证和源相机识别的文献中。传感器图案噪声在频率内容方面携带的丰富信息使其独一无二，因此适合源相机识别。估计传感器图案噪声的传统方法使用一组图像来估计每个图像的图案残留信号。然后对估计的残余信号进行平均以获得传感器图案噪声。这是基于这样的假设：每个残余信号是传感器图案噪声的噪声观察。这种假设在实践中是合理的，因为图像是在不同条件下采集的，使得相应的残留信号彼此不同。例如，亮图像比暗图像提供更好的传感器图案噪声估计。此外，饱和像素会在残留信号中产生不希望有的噪声。受这一观察的启发，提出了一种加权平均方法来进行有效的传感器模式噪声估计。所提出的方法已通过文献中的两种传感器模式噪声估计技术进行了验证，并且实验结果显示了显着的改进。
Sensor pattern noise has been broadly used in the literature for image authentication and source camera identification. The abundant information that a sensor pattern noise carries in terms of the frequency content makes it unique and hence suitable for source camera identification. The traditional approach for estimating the sensor pattern noise uses a set of images to estimate a pattern residual signal from each image. The estimated residual signals are then averaged to obtain the sensor pattern noise. This is based on the assumption that each residual signal is a noisy observation of the sensor pattern noise. Such an assumption is well justified in practice because the images are acquired under different conditions making the corresponding residual signals distinct from each other. For instance bright images provide better sensor pattern noise estimation than dark images. Also, saturated pixels cause undesirable noise in residual signals. Inspired by this observation, a weighted averaging approach is proposed for efficient sensor pattern noise estimation. The proposed approach has been validated with two sensor pattern noise estimation techniques from the literature and significant improvements have been shown through experimental results.