基于DCT系数首位马尔可夫模型的双压缩检测

Lisha Dong, Xiangwei Kong, Bo Wang, Xingang You
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引用次数: 13

摘要

双重压缩通常发生在图像经过某种篡改之后,因此双重压缩检测是评估给定图像真实性的基本手段。本文提出利用马尔可夫转移概率矩阵对离散余弦变换(DCT)系数基于模态第一位数的分布进行建模,并利用其平稳分布作为双重压缩检测的特征。实验结果表明了该方法的有效性,并通过比较表明了采用该二阶统计模型的改进。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Double Compression Detection Based on Markov Model of the First Digits of DCT Coefficients
Double compression usually occurs after the image has gone through some kinds of tampering, so double compression detection is a basic mean to assess the authenticity of a given image. In this paper, we propose to model the distribution of the mode based first digits of DCT (Discrete Cosine Transform) coefficients using Markov transition probability matrix and utilize its stationary distribution as features for double compression detection. Experiment results show the effectiveness of the proposed method and comparison has been made to show the improvement by using this second order statistical model.
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