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Volume: 2 | Article ID: art00099
PCA Component Mixing for Watermark Embedding in Spectral Images
  DOI :  10.2352/CGIV.2004.2.1.art00099  Published OnlineJanuary 2004

This study considers watermark embedding in spectral images. The embedding takes place in a transform space which is obtained through the Principal Component Analysis (PCA). The watermark is embedded in one eigenimage by mixing one eigenimage and the watermark. The watermark is a visual watermark which spreads to all bands of the image after the inverse PCA-transform. This new method is a generalization of an existing method. Our experiments indicate that a suitable set of parameter values allows better embedding than the methods compared.

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Arto Kaarna, Vladimir Botchko, Pavel Galibarov, "PCA Component Mixing for Watermark Embedding in Spectral Imagesin Proc. IS&T CGIV 2004 Second European Conf. on Colour in Graphics, Imaging, and Vision,  2004,  pp 494 - 498,

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