Channel models for high-capacity information hiding in images

We consider the scenario of blind information hiding in images as a communications channel, where the channel noise is caused by the embedding and blind extraction method as well as by any lossy compression method utilized to store and transmit the image. We assume that the objectives of the information hiding method are the maximization of payload and its visual and statistical imperceptibility; also, we assume that the warden is passive. For the specific method of Spread Spectrum Image Steganography (SSIS) we show that the channel can be modeled as a Laplacian distribution, and use this to estimate the channel SNR to be expected for any given signal embedding strength by applying the technique to a range of typical images. Finally, we model the effects of various signal extraction methods and lossy compression. This allows a fair comparison with respect to payload capacity. The results shown in this paper are useful for maximizing the channel usage.