PROJECT TITLE :

Statistical Model of JPEG Noises and Its Application in Quantization Step Estimation - 2015

ABSTRACT:

During this paper, we present a statistical analysis of JPEG noises, together with the quantization noise and therefore the rounding noise during a JPEG compression cycle. The JPEG noises in the first compression cycle are well studied; however, so far less attention has been paid on the statistical model of JPEG noises in higher compression cycles. Our analysis reveals that the noise distributions in higher compression cycles are totally different from those in the first compression cycle, and they are hooked in to the quantization parameters used between 2 successive cycles. To demonstrate the advantages from the analysis, we have a tendency to apply the statistical model in JPEG quantization step estimation. We tend to construct a sufficient statistic by exploiting the derived noise distributions, and justify that the statistic has many special properties to reveal the ground-truth quantization step. Experimental results demonstrate that the proposed estimator can uncover JPEG compression history with a satisfactory performance.


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