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Downscaling Factor Estimation on Pre-JPEG Compressed Images
IEEE Transactions on Circuits and Systems for Video Technology ( IF 8.3 ) Pub Date : 2020-03-01 , DOI: 10.1109/tcsvt.2019.2893353
Xianjin Liu , Wei Lu , Qin Zhang , Jiwu Huang , Yun-Qing Shi

Resampling detection is one of the most important topics in image forensics, and the most widely used method in resampling detection is spectral analysis. Since JPEG is the most widely used image format, it is reasonable that the resampling operation is processed on JPEG images. JPEG block artifacts bring severe interference to spectrum-based methods and degrade the detection performance. In addition, the spectral characteristics of the downscaling scenarios are very weak. The detection of downscaling still presents a considerable challenge to forensic applications. In this paper, we propose a method to estimate the downscaling factors of pre-JPEG compressed images in the presence of image downscaling after JPEG compressions. We first analyze the spectrum of scaled images and give an exact formulation of how the scaling factors influence the appearance of periodic artifacts. The expected positions of the characteristic resampling peaks are analytically derived. For the downscaling scenario, the shifted JPEG block artifacts produce periodic peaks, which cause misdetection in the characteristic peak. We find that the interval between the adjacent extrema of difference images obeys the geometric distribution and the distribution has periodic peaks for JPEG images. Hence, we adopt the difference image extremum interval histogram and combine the spectral method to obtain the final estimation. The experimental results demonstrate that the proposed detection method outperforms some state-of-the-art methods.

中文翻译:

Pre-JPEG 压缩图像的降尺度因子估计

重采样检测是图像取证中最重要的课题之一,重采样检测中应用最广泛的方法是光谱分析。由于JPEG是使用最广泛的图像格式,因此对JPEG图像进行重采样操作是合理的。JPEG 块伪影给基于频谱的方法带来严重干扰并降低检测性能。此外,降尺度场景的光谱特性非常弱。降尺度的检测仍然对取证应用提出了相当大的挑战。在本文中,我们提出了一种在 JPEG 压缩后存在图像缩小的情况下估计 JPEG 前压缩图像的缩小因子的方法。我们首先分析缩放图像的频谱,并给出缩放因子如何影响周期性伪影外观的精确公式。特征重采样峰的预期位置是通过分析推导出来的。对于降尺度场景,移位的 JPEG 块伪影会产生周期性峰值,这会导致特征峰值中的误检测。我们发现差值图像的相邻极值之间的间隔服从几何分布,并且对于JPEG图像该分布具有周期性的峰值。因此,我们采用差分图像极值区间直方图并结合谱法来获得最终估计。实验结果表明,所提出的检测方法优于一些最先进的方法。特征重采样峰的预期位置是通过分析推导出来的。对于降尺度场景,移位的 JPEG 块伪影会产生周期性峰值,这会导致特征峰值中的误检测。我们发现差值图像的相邻极值之间的间隔服从几何分布,并且对于JPEG图像该分布具有周期性的峰值。因此,我们采用差分图像极值区间直方图,并结合谱法来获得最终估计。实验结果表明,所提出的检测方法优于一些最先进的方法。特征重采样峰的预期位置是通过分析推导出来的。对于降尺度场景,移位的 JPEG 块伪影会产生周期性峰值,这会导致特征峰值中的误检测。我们发现差值图像的相邻极值之间的间隔服从几何分布,并且对于JPEG图像该分布具有周期性的峰值。因此,我们采用差分图像极值区间直方图并结合谱法来获得最终估计。实验结果表明,所提出的检测方法优于一些最先进的方法。我们发现差值图像的相邻极值之间的间隔服从几何分布,并且对于JPEG图像该分布具有周期性的峰值。因此,我们采用差分图像极值区间直方图并结合谱法来获得最终估计。实验结果表明,所提出的检测方法优于一些最先进的方法。我们发现差值图像的相邻极值之间的间隔服从几何分布,并且对于JPEG图像该分布具有周期性的峰值。因此,我们采用差分图像极值区间直方图并结合谱法来获得最终估计。实验结果表明,所提出的检测方法优于一些最先进的方法。
更新日期:2020-03-01
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