Increasing Trust in Image Analysis by Detecting Trellis Quantization in JPEG Images

JPEG image forensics investigates the authenticity and origin of compressed images. Many established methods rely on assumptions about the statistical distribution of quantized discrete cosine transform coefficients. However, JPEG implementations that use trellis quantization, such as mozjpeg, produce images that challenge these assumptions. In this study, we demonstrate that artifacts resulting from trellis quantization can compromise the reliability of established forensic methods and cause false alarms for innocuous images. We address this issue by presenting methods to detect trellis artifacts and validating their robustness in scenarios commonly encountered in forensic analyses.