Learn More
We propose a statistical model of natural images in JPEG format. The image acquisition is composed of three principal stages. First, a RAW image is obtained from sensor of Digital Still Cameras (DSC). Then, the RAW image is subject to some post-acquisition processes such as demosaicking, white-balancing and γ-correction to improve its visual quality.(More)
This paper investigates the detection of information hidden in digital media by the least significant bit (LSB) matching scheme. In a theoretical context of known medium parameters, two important results are presented. First, based on the likelihood ratio test, we present a test that asymptotically maximizes the detection power whatever the embedding rate(More)
The goal of this paper is to design a statistical test for the camera model identification problem. The approach is based on the heteroscedastic noise model, which more accurately describes a natural raw image. This model is characterized by only two parameters, which are considered as unique fingerprint to identify camera models. The camera model(More)
The goal of this paper is to propose the optimal statistical test based on the modeling of discrete cosine transform (DCT) coefficients with a quantified Laplacian distribution. This paper focuses on the detection of hidden information embedded in bits of the DCT coefficients of a JPEG image. This problem is difficult, in terms of statistical decision, for(More)
In the last two decades substantial progress has been made in the detection of hidden information or hidden communication channels in media files or streams. Typically, it is necessary to reliably detect in a huge set of files (image, audio, and video) which of these files contain the hidden information. The goal of this paper is to study the problem of(More)
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(More)
This paper investigates the reliable detection of information embedded with the least significant bits (LSB) matching scheme. It is aimed to design a test with analytically predictable error probabilities. To this end, the problem of hidden information detection is cast in the framework of hypothesis testing theory. In order to deal with nuisance parameters(More)