Digital Image Watermarking Using Balanced Multiwavelets

(2006) Digital Image Watermarking Using Balanced Multiwavelets. IEEE Transactions on Signal Processing, 54 (4). pp. 1519-1536.

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In this paper, a robust watermarking algorithm using balanced multiwavelet transform is proposed. The latter transform achieves simultaneous orthogonality and symmetry without requiring any input prefiltering. Therefore, considerable reduction in computational complexity is possible, making this transform a good candidate for real-time watermarking implementations such as audio broadcast monitoring and DVD video watermarking. The embedding scheme is image adaptive using a modified version of a well-established perceptual model. Therefore, the strength of the embedded watermark is controlled according to the local properties of the host image. This has been achieved by the proposed perceptual model, which is only dependent on the image activity and is not dependent on the multifilter sets used, unlike those developed for scalar wavelets. This adaptivity is a key factor for achieving the imperceptibility requirement often encountered in watermarking applications. In addition, the watermark embedding scheme is based on the principles of spread-spectrum communications to achieve higher watermark robustness. The optimal bounds for the embedding capacity are derived using a statistical model for balanced multiwavelet coefficients of the host image. The statistical model is based on a generalized Gaussian distribution. Limits of data hiding capacity clearly show that balanced multiwavelets provide higher watermarking rates. This increase could also be exploited as a side channel for embedding watermark synchronization recovery data. Finally, the analytical expressions are contrasted with experimental results where the robustness of the proposed watermarking system is evaluated against standard watermarking attacks.

Item Type: Article
Uncontrolled Keywords: Balanced multiwavelets, data hiding, embedding capacity, game theory, image watermarking, information theory, scalar wavelets
Subjects: Computer
Department: College of Computing and Mathematics > Information and Computer Science
Depositing User: LAHOUARI GHOUTI
Date Deposited: 18 Jun 2008 08:10
Last Modified: 01 Nov 2019 13:26