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Detection of median filtering based on ARMA model and pixel-pair histogram feature of difference image

机译：基于ARMA模型的中值滤波和差异图像的像素对直方图特征的检测

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摘要

Median filtering is a widely used method for removing noise and smoothing regions of an image, and the detection of median filtering has drawn much attention from researchers of image forensic. A new robust detection scheme of median filtering based on pixel-pair histogram (PPH) and coefficients of autoregressive moving average model (ARMA) of difference image is proposed in this paper. In the proposed scheme, the PPH and ARMA are extracted from the difference image in four directions; the generated PPH-ARMA feature of 396 dimensions can effectively be used to detect the median filtering. In order to verify the effectiveness of the proposed scheme, a series of experiments on single database and compound databases are conducted, and the experimental results show that, the proposed scheme outperforms many existing algorithms. Moreover, the suggested approach achieves best performance in single dataset and multiple compound datasets compared with state-of-the-art methods, especially for strong JPEG compression and low resolution images.
机译：中值过滤是一种广泛使用的方法，用于去除图像的噪声和平滑区域，并且中值过滤的检测从图像法医的研究人员中汲取了很多关注。本文提出了一种基于像素对直方图（PPH）的中值滤波的新的鲁棒检测方案，并在本文中提出了差异图像的自回归移动平均模型（ARMA）的系数。在所提出的方案中，PPH和ARMA在四个方向上从差异图像中提取;产生396尺寸的产生的PPH-ARMA功能可以有效地用于检测中值滤波。为了验证所提出的方案的有效性，进行了一系列关于单一数据库和复合数据库的实验，实验结果表明，所提出的方案优于许多现有算法。此外，建议的方法与最先进的方法相比，在单个数据集和多个复合数据集中实现了最佳性能，特别是对于强大的JPEG压缩和低分辨率图像。

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