计算机工程 ›› 2012, Vol. 38 ›› Issue (01): 217-219.doi: 10.3969/j.issn.1000-3428.2012.01.070

• 图形图像处理 • 上一篇    下一篇

一种适用于有损压缩图像的重采样检测算法

陈孟原,李 峰,殷苌茗   

  1. (长沙理工大学计算机与通信工程学院,长沙 410114)
  • 收稿日期:2011-05-27 出版日期:2012-01-05 发布日期:2012-01-05
  • 作者简介:陈孟原(1986-),女,硕士,主研方向:图像处理,信息安全;李 峰、殷苌茗,教授、博士
  • 基金项目:
    国家自然科学基金资助项目(60973113);湖南省自然科学基金资助项目(09JJ3120)

Resampling Detection Algorithm for Lossy Compression Image

CHEN Meng-yuan, LI Feng, YIN Chang-ming   

  1. (School of Computer and Telecommunications Engineering, Changsha University of Science and Technology, Changsha 410114, China)
  • Received:2011-05-27 Online:2012-01-05 Published:2012-01-05

摘要: 有损压缩与重采样操作在图像像素间产生的相关统计特性导致有损压缩图像难以被检测。为解决该问题,提出一种适用于无损图像的重采样检测算法,利用插值信号的周期性对图像频域特征进行分析,通过估算插值系数实现重采样检测。实验结果表明,该算法鲁棒性强、应用范围广,对于JPEG有损压缩图像的重采样检测具有较高的正确率。

关键词: 有损压缩, 快速傅里叶变换, 重采样检测, 统计特性, 数字图像取证

Abstract: The similar statistical properties between pixels in lossy compression and resampling operation makes the lossy compression image hard to detection. In order to solve the problem, this paper presents a resampling detection algorithm which is applied to lossless compression. It investigates the spectrum characteristics of an image by analyzing the periodicity of interpolating signal and then estimate interpolation coefficient of the image resampling. Experimental results indicate that this algorithm has strong robustness and wide application, and it has precision rate for JPEG lossy compression image resampling detection.

Key words: lossy compression, Fast Fourier Transform(FFT), resampling detection, statistical property, digital image forensics

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