Contrast Enhancement Estimation for Digital Image Forensics
This work addresses digital image forensics for detecting manipulated images, representing an incremental improvement with specific robustness to noise.
The paper tackles the problem of detecting image forgeries by developing a method to estimate contrast enhancement from a single image, recovering the original pixel histogram and enhancement simultaneously with an iterative algorithm that is robust to additive noise, and also detects regions with different contrast enhancements to identify composite images.
Inconsistency in contrast enhancement can be used to expose image forgeries. In this work, we describe a new method to estimate contrast enhancement from a single image. Our method takes advantage of the nature of contrast enhancement as a mapping between pixel values, and the distinct characteristics it introduces to the image pixel histogram. Our method recovers the original pixel histogram and the contrast enhancement simultaneously from a single image with an iterative algorithm. Unlike previous methods, our method is robust in the presence of additive noise perturbations that are used to hide the traces of contrast enhancement. Furthermore, we also develop an e effective method to to detect image regions undergone contrast enhancement transformations that are different from the rest of the image, and use this method to detect composite images. We perform extensive experimental evaluations to demonstrate the efficacy and efficiency of our method method.