# Differential Imaging Forensics

## TL;DR

This paper presents differential imaging forensics (DIF), a new technique that extracts faint visual evidence from images and videos by comparing them with reference images, aiding in detecting forgeries and deep fakes.

## Contribution

The paper introduces DIF, a novel forensic method that computationally amplifies subtle visual evidence through differential analysis, enabling detection of forgeries and deep fakes.

## Key findings

- DIF successfully extracts faint visual evidence in practical experiments.
- DIF enhances detection of forged images and videos.
- The method reveals evidence invisible to the human eye.

## Abstract

We introduce some new forensics based on differential imaging, where a novel category of visual evidence created via subtle interactions of light with a scene, such as dim reflections, can be computationally extracted and amplified from an image of interest through a comparative analysis with an additional reference baseline image acquired under similar conditions. This paradigm of differential imaging forensics (DIF) enables forensic examiners for the first time to retrieve the said visual evidence that is readily available in an image or video footage but would otherwise remain faint or even invisible to a human observer. We demonstrate the relevance and effectiveness of our approach through practical experiments. We also show that DIF provides a novel method for detecting forged images and video clips, including deep fakes.