PCA component mixing for watermark embedding in spectral images

被引：0

作者：

Kaarna, A ^{[1
]}

Botchko, V ^{[1
]}

Galibarov, P ^{[1
]}

机构：

[1] Lappeenranta Univ Technol, Dept Informat Technol, FIN-53851 Lappeenranta, Finland

来源：

CGIV 2004: SECOND EUROPEAN CONFERENCE ON COLOR IN GRAPHICS, IMAGING, AND VISION - CONFERENCE PROCEEDINGS | 2004年

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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.

引用

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页码：494 / 498

页数：5

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