Quantized projection data hiding

10 years 5 months ago
Quantized projection data hiding
In this paper we propose a novel data hiding procedure called Quantized Projection (QP), that combines elements from quantization (i.e. Quantization Index Modulation, QIM) and spread-spectrum methods. The method is based in quantizing a diversity projection of the host signal, inspired in the statistic used for detection in spread-spectrum algorithms. We carry on a theoretical analysis of QP together with its empirical validation to rigorously show that it offers an excellent performance: QP features probabilities of decoding error several orders of magnitude lower than the aforementioned families of methods for the same dimensionality (diversity) and attacking distortion level. In addition we introduce a Costa-based improvement of the basic QP method named Distortion Compensated QP.
Fernando Pérez-González, Féli
Added 24 Oct 2009
Updated 24 Oct 2009
Type Conference
Year 2002
Where ICIP
Authors Fernando Pérez-González, Félix Balado
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