Quantized projection data hiding
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 on quantizing a diversity projection of the host signal, inspired in the statistic used for detection in spread-spectrum algorithms. We carry out a theoretical analysis of QP together with its empirical validation to show rigorously 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 (see Costa, M.H.M., IEEE Trans. on Inf. Theory, vol.29, no.3, p.439-41, 1983) of the basic QP method named distortion compensated QP.