Multimedia Tools and Applications

, Volume 76, Issue 15, pp 16563–16580 | Cite as

Image sharpening detection based on multiresolution overshoot artifact analysis

  • Nan Zhu
  • Cheng DengEmail author
  • Xinbo Gao


With the wide use of sophisticated photo editing tools, digital image manipulation becomes very convenient, which makes the detection of image tampering significant. Image sharpening, which aims to enhance the contrast of edges in an image, is a ubiquitous image tampering operation. The detection of image sharpening can serve as a reliable clue for image forgery. In this paper, we propose a novel image sharpening detection method based on multiresolution overshoot artifact analysis (MOAA). By building the relationship between the overshoot artifact strength and the slope of a sharpened edge, we find that although undergoing the same sharpening operation, the edge with large slope will present a stronger overshoot artifact than the one with small slope. Based on this finding, we use the nonsubsampled contourlet transform (NSCT) to classify the image edge points into three categories, i.e., weak, middle and strong edge points and measure the overshoot artifact of each category respectively. A cascaded decision strategy is adopted to decide an image is sharpened or not. Experimental results on digital images with various sharpening operators demonstrate the superiority of our proposed method when compared with state-of-the-art approaches.


Image forensics Image sharpening detection Nonsubsampled contourlet transform Overshoot artifacts 



The authors would like to thank the Editor-in-Chief, the handling associate editor and all anonymous reviewers for their considerations and suggestions. This work was supported by the National High Technology Research and Development Program of China (2013AA01A602), the National Natural Science Foundation of China (Grant Nos. 61432014 and 61572388) and Program for Changjiang Scholars and Innovative Research Team in University (No. IRT13088).


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Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  1. 1.School of Electronic EngineeringXidian UniversityXi’anChina

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