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Steganography using Gibbs random fields
2010
Proceedings of the 12th ACM workshop on Multimedia and security - MM&Sec '10
Many steganographic algorithms for empirical covers are designed to minimize embedding distortion. In this work, we provide a general framework and practical methods for embedding with an arbitrary distortion function that does not have to be additive over pixels and thus can consider interactions among embedding changes. The framework evolves naturally from a parallel made between steganography and statistical physics. The Gibbs sampler is the key tool for simulating the impact of optimal
doi:10.1145/1854229.1854266
dblp:conf/mmsec/FillerF10
fatcat:4iy4xvfrpncydjtbwwq27c2vfe