Principles and practice of information theory
Principles and practice of information theory
Fundamentals of digital image processing
Fundamentals of digital image processing
Elements of information theory
Elements of information theory
An introduction to signal detection and estimation (2nd ed.)
An introduction to signal detection and estimation (2nd ed.)
A Unified and Generalized Treatment of Authentification Theory
STACS '96 Proceedings of the 13th Annual Symposium on Theoretical Aspects of Computer Science
Detecting Hidden Messages Using Higher-Order Statistics and Support Vector Machines
IH '02 Revised Papers from the 5th International Workshop on Information Hiding
DCC '97 Proceedings of the Conference on Data Compression
MGMM: Multiresolution Gaussian Mixture Models for Computer Vision
ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 1
Blind statistical steganalysis of additive steganography using wavelet higher order statistics
CMS'05 Proceedings of the 9th IFIP TC-6 TC-11 international conference on Communications and Multimedia Security
The edge process model and its application to information-hiding capacity analysis
IEEE Transactions on Signal Processing
Analysis of multiresolution image denoising schemes using generalized Gaussian and complexity priors
IEEE Transactions on Information Theory
Image subband coding using context-based classification and adaptive quantization
IEEE Transactions on Image Processing
A framework for evaluating the data-hiding capacity of image sources
IEEE Transactions on Image Processing
On exploiting geometric constraint of image wavelet coefficients
IEEE Transactions on Image Processing
Distributed keyless security for correlated data with applications in visual sensor networks
Proceedings of the 9th workshop on Multimedia & security
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In this paper we consider the problem of performance improvement of non-blind statistical steganalysis of additive steganography in real images. The proposed approach differs from the existing solutions in two main aspects:(a) a locally non-stationary Gaussian model is introduced via source splitting to represent the statistics of the cover image and (b)the detection of the hidden information is performed not from all but from those channels that allow to perform it with the required accuracy. We analyze the theoretically attainable bounds in such a framework and compare them to the corresponding limits of the existing state-of-the-art frameworks. The performed analysis demonstrates the superiority of the proposed approach.