The goal of this paper is to propose a statistical model of quantized discrete cosine transform (DCT) coefficients. It relies on a mathematical framework of studying the image processing pipeline of a typical digital camera instead of fitting empirical data with a variety of popular models proposed in this paper. To highlight the accuracy of the proposed model, this paper exploits it for the detection of hidden information in JPEG images. By formulating the hidden data detection as a hypothesis testing, this paper studies the most powerful likelihood ratio test for the steganalysis of Jsteg algorithm and establishes theoretically its statistical performance. Based on the proposed model of DCT coefficients, a maximum likelihood estimator for embedding rate is also designed. Numerical results on simulated and real images emphasize the accuracy of the proposed model and the performance of the proposed test.
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