A Statistical model for quantized AC block DCT coefficients in JPEG compression and its application to detecting potential compression history in bitmap images

Authors:
Gopal Narayanan;Yun Qing Shi
Affiliations:
Department of Electrical and Computer Engineering, New Jersey Institute of Technology, Newark, New Jersey;Department of Electrical and Computer Engineering, New Jersey Institute of Technology, Newark, New Jersey
Venue:
IWDW'10 Proceedings of the 9th international conference on Digital watermarking
Year:
2010

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Abstract

We first develop a probability mass function (PMF) for quantized block discrete cosine transform (DCT) coefficients in JPEG compression using statistical analysis of quantization, with a Generalized Gaussian model being considered as the PDF for non-quantized block DCT coefficients. We subsequently propose a novel method to detect potential JPEG compression history in bitmap images using the PMF that has been developed. We show that this method outperforms a classical approach to compression history detection in terms of effectiveness. We also show that it detects history with both independent JPEG group (IJG) and custom quantization tables.