Abstract
Double compression of images occurs when one compresses twice, possibly with different quality factors, a digital image. Estimation of the first compression parameter of such a double compression is of a crucial interest for image forensics since it may help revealing, for instance, the software or the source camera. This paper proposes an accurate method for estimating the primary quantization steps in double-compressed JPEG images. This original methodology is based on an accurate statistical model of discrete cosine transform (DCT) coefficients that has been proposed in our previous works. We also present a thorough analysis of the double compression properties, taking into account carefully the effect of round-off noise. This analysis is used to derive an accurate range of possible value for quantization of primary DCT coefficients with respect to the secondary quantization step. Using both the statistical model of quantized DCT coefficients and the range of possible values of first quantization step, a model of the twice quantized DCT coefficients is established. Eventually, it is proposed to estimate the primary quantization value by finding, among a set of possible candidates, the one that best match the proposed statistical model in terms of minimal symmetrized Kullback-Leibler (KL) divergence. The numerical experiments on large databases of real images and comparisons with state-of-the-art approaches emphasize the relevance of the proposed method.
Highlights
The evolution of digital imaging and information technologies in the past decades has raised a number of information security challenges
JPEG images are involved in many forensics issues, such as authenticity of JPEG compression history [2], steganalysis [3] or image forgery detection [4]
In contrast with prior statistical model-based methods, this paper proposes to exploit the state-of-the-art statistical model of once-quantized discrete cosine transform (DCT) coefficients that has been established in our previous works [16]–[18]
Summary
The evolution of digital imaging and information technologies in the past decades has raised a number of information security challenges. This model is used together with a study of quantization and impact to propose a statistical model of double JPEG-compressed image DCT coefficients Based on this model and on the impact of quantization a method is proposed for estimating with high accuracy the VOLUME 7, 2019. This paper statistically analyze double JPEG compression properties and takes into account the effect of round-off noise, establishes a proper range of values of primary DCT coefficients with respect to the secondary quantization step. Based on this range, the distribution of the secondary DCT coefficients is derived. Throughout this paper, we will use lower case characters, such as x to represent real and integer values and upper case (except for Greek letters) boldface characters X to represent matrices
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