This work reduces the computational requirements of the additive noise steganalysis presented by Harmsen and Pearlman. The additive noise model assumes that the stegoimage is created by adding a pseudo-noise to a coverimage. This addition predictably alters the joint histogram of the image. In color images it has been shown that this alteration can be detected using a three-dimensional Fast Fourier Transform (FFT) of the histogram. As the computation of this transform is typically very intensive, a method to reduce the required processing is desirable. By considering the histogram between pairs of channels in RGB images, three separate two-dimensional FFTs are used in place of the original three-dimensional FFT. This method is shown to offer computational savings of approximately two orders of magnitude while only slightly decreasing classification accuracy.
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