Improved forgery detection with lateral chromatic aberration

Abstract

In this paper we propose a technique to improve the accuracy of lateral chromatic aberration (LCA) based detection of copy-paste image forgeries. We propose a statistical model of the error between local estimates of LCA displacement vectors and those predicted by a global model. Using this statistical model, we formulate forgery detection as a hypothesis testing problem, and derive the optimal detection statistic for performing LCA-based forgery detection. Through a series of experiments, we demonstrate that our proposed technique outperforms existing approaches for conducting LCA-based forgery detection.