论文标题
深入的DCT系数分布分析进行首次量化估计
In-Depth DCT Coefficient Distribution Analysis for First Quantization Estimation
论文作者
论文摘要
JPEG双重压缩图像中对痕迹的开发对于调查至关重要。可以正确利用此类见解，可以执行第一个量化估计（FQE），以获得源相机模型标识（CMI），从而重建数字图像的历史记录。在本文中，提出了一种能够使用混合的统计和机器学习方法来估算JPEG双重压缩图像的第一个量化因子的方法。证明所提出的解决方案可起作用，而没有任何关于量化矩阵的A-Priori假设。实验结果和与最先进的比较表明了提出的技术的好处。
The exploitation of traces in JPEG double compressed images is of utter importance for investigations. Properly exploiting such insights, First Quantization Estimation (FQE) could be performed in order to obtain source camera model identification (CMI) and therefore reconstruct the history of a digital image. In this paper, a method able to estimate the first quantization factors for JPEG double compressed images is presented, employing a mixed statistical and Machine Learning approach. The presented solution is demonstrated to work without any a-priori assumptions about the quantization matrices. Experimental results and comparisons with the state-of-the-art show the goodness of the proposed technique.
