Detecting median filtering via two-dimensional AR models of multiple filtered eesiduals

	Detecting median filtering via two-dimensional AR models of multiple filtered eesiduals
	Jianquan Yang; Honglei Ren; Guopu Zhu; Jiwu Huang; Yun-Qing Shi
刊名	Multimedia Tools and Applications
	2017
文献子类	期刊论文
英文摘要	Median filtering, being an order statistic filtering, has been widely used in image denoising and recently also in image anti-forensics and anti-steganalysis. In the past few years, several methods have been developed for median filtering detection. However, it is still a challenging task to detect median filtering in JPEG compressed images. In this paper, we propose a novel method to solve this challenging task. We first generate median filtered residual (MFR), average filtered residual (AFR) and Gaussian filtered residual (GFR) by calculating the differences between an original image and its filtered images. Then, we propose to use two-dimensional autoregressive (2D-AR) model to characterize MFR, AFR and GFR separately, and further combine the 2D-AR coefficients of these three residuals into a set of features. Finally, the extracted feature set is fed into a support vector machine classifier for training and detection. Extensive experiments have demonstrated that compared with existing methods, the proposed one can achieve a considerable improvement in detecting median filtering in heavily compressed images.
URL标识	查看原文
语种	英语
内容类型	期刊论文
源URL	[http://ir.siat.ac.cn:8080/handle/172644/12554]
专题	深圳先进技术研究院_数字所
作者单位	Multimedia Tools and Applications
推荐引用方式 GB/T 7714	Jianquan Yang,Honglei Ren,Guopu Zhu,et al. Detecting median filtering via two-dimensional AR models of multiple filtered eesiduals[J]. Multimedia Tools and Applications,2017.
APA	Jianquan Yang,Honglei Ren,Guopu Zhu,Jiwu Huang,&Yun-Qing Shi.(2017).Detecting median filtering via two-dimensional AR models of multiple filtered eesiduals.Multimedia Tools and Applications.
MLA	Jianquan Yang,et al."Detecting median filtering via two-dimensional AR models of multiple filtered eesiduals".Multimedia Tools and Applications (2017).