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The Influence of the Image Basis on Modeling and Steganalysis Performance

MPG-Autoren
http://pubman.mpdl.mpg.de/cone/persons/resource/persons84203

Schwamberger,  V
Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons84193

Le PHD, Schölkopf,  B
Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons83919

Franz,  MO
Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Zitation

Schwamberger, V., Le PHD, Schölkopf, B., & Franz, M. (2010). The Influence of the Image Basis on Modeling and Steganalysis Performance. Information Hiding:12th International Conference (IH 2010), 133-144.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-0013-BFA6-5
Zusammenfassung
We compare two image bases with respect to their capabilities for image modeling and steganalysis. The first basis consists of wavelets, the second is a Laplacian pyramid. Both bases are used to decompose the image into subbands where the local dependency structure is modeled with a linear Bayesian estimator. Similar to existing approaches, the image model is used to predict coefficient values from their neighborhoods, and the final classification step uses statistical descriptors of the residual. Our findings are counter-intuitive on first sight: Although Laplacian pyramids have better image modeling capabilities than wavelets, steganalysis based on wavelets is much more successful. We present a number of experiments that suggest possible explanations for this result.