Exposing image forgery through the detection of contrast enhancement

Xufeng Lin, Chang‐Tsun Li, Yongjian Hu · 2013

In this paper, a novel forensic method of exposing cut-and-paste image forgery through detecting contrast enhancement is proposed. We reveal the inter-channel correlation introduced by color image interpolation, and show how a linear or nonlinear contrast enhancement can disturb this natural inter-channel dependency. We then construct a metric to measure these correlations, which are useful in distinguishing the original and contrast enhanced images. The effectiveness of the proposed algorithm is experimentally validated on natural color images captured by commercial cameras. Finally, its robustness against some anti-forensic algorithms is also discussed.

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