The Center for Education and Research in Information Assurance and Security (CERIAS)

The Center for Education and Research in
Information Assurance and Security (CERIAS)

Lapped-orthogonal-transform-based adaptive image watermarking

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Author

Yuxin Liu and Bin Ni and Xiaojun Feng and Edward J. Delp

Entry type

article

Abstract

A robust, invisible watermarking scheme is proposed for digital images, where the watermark is embedded using the block-based lapped orthogonal transform (LOT). The embedding process follows a spread spectrum watermarking approach. In contrast to the use of transforms such as discrete cosine transform, our LOT watermarking scheme allows larger watermark embedding energy while maintaining the same level of subjective invisibility. In particular, the use of LOT reduces block artifacts caused by the insertion of the watermark in a block-by-block manner, hence obtaining a better balance between invisibility and robustness. Moreover, we use a human visual system (HVS) model to adaptively adjust the energy of the watermark during embedding. In our HVS model, each block is categorized into one of four classes (texture, fine-texture, edge, and plain-area) by using a feature known as the texture masking energy. Blocks with edges are also classified according to the edge direction. The block classification is used to adjust the watermark embedding parameters for each block.

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Date

2006

Journal

Journal of Electronic Imaging

Key alpha

liu:013009

Number

1

Pages

013009

Publisher

SPIE

Volume

15

Affiliation

Purdue University

Publication Date

2006-01-01

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