JPEG anti-forensics using non-parametric DCT quantization noise estimation and natural image statistics

Abstract

This paper proposes an anti-forensic method that disguises the footprints left by JPEG compression, whose objective is to fool existing JPEG forensic detectors while keeping a high visual quality of the processed image. First we examine the reliability of existing detectors and point out the potential vulnerability of the quantization table estimation based detector. Then we construct a new, non-parametric method to DCT histogram smoothing without any histogram statistical model. Finally JPEG forensic detectors are fooled by optimizing an objective function considering both the anti-forensic terms and a natural image statistical model. We show that compared to the state-of-the-art methods the proposed JPEG anti-forensic method is able to achieve a higher image visual quality while being undetectable under existing detectors.