PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

The Influence of the Image Basis on Modeling and Steganalysis Performance
Valentin Schwamberger, Pham Hai Dang Le, Bernhard Schölkopf and Matthias O. Franz
In: 12th Information Hiding Conference, 28-30 June 2010, Calgary, Alberta, Canada.

Abstract

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.

EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Computational, Information-Theoretic Learning with Statistics
Learning/Statistics & Optimisation
Brain Computer Interfaces
Theory & Algorithms
ID Code:7798
Deposited By:Bernhard Schölkopf
Deposited On:17 March 2011