A Reliable JPEG Quantization Table Estimator
Tina Nikoukhah, Miguel Colom, Jean-Michel Morel, Rafael Grompone von Gioi
Tina Nikoukhah, Miguel Colom, Jean-Michel Morel, and Rafael Grompone von Gioi, A Reliable JPEG Quantization Table Estimator, Image Processing On Line, 12 (2022), pp. 173–197. https://doi.org/10.5201/ipol.2022.399

Communicated by Jose-Luis Lisani
Demo edited by Tina Nikoukhah


JPEG compression is a commonly used method of lossy compression for digital images. The degree of compression can be adjusted by the choice of a quality factor QF. Each software associates this value to a quantization table, which is an 8 x 8 matrix used to quantize the DCT coefficients of an image. We propose a method for recovering the JPEG quantization table relying only on the image information, without any metadata from the file header; thus the proposed method can be applied to an uncompressed image format to detect a previous JPEG compression. A statistical validation is used to decide whether significant quantization traces are found or not, and to provide a quantitative measure of the confidence on the detection.