Improvement of noise stability of spread-spectrum steganography methods utilizing singular and spectral decomposition of cover matrix.
New steganography spread-spectrum (SS) methods increasing the noise stability of algorithms that exploit the singular value decomposition and the spectrum decomposition of a cover matrix image are proposed. The minimum-eigenvalue eigenvector of the singular values vector or eigenvalues vector host data autocorrelation matrix is treated as the embedding signal vector.