Bhowmik, D. and Abhayaratne, C. orcid.org/0000-0002-2799-7395 (2019) Embedding distortion analysis in wavelet-domain watermarking. ACM Transactions on Multimedia Computing, Communications, and Applications, 15 (4). 108. ISSN 1551-6857
Abstract
Imperceptibility and robustness are two complementary fundamental requirements of any watermarking algorithm. Low-strength watermarking yields high imperceptibility, but exhibits poor robustness. High-strength watermarking schemes achieve good robustness but often infuse distortions resulting in poor visual quality in host images. This article analyses the embedding distortion for wavelet-based watermarking schemes. We derive the relationship between distortion, measured in mean square error (MSE), and the watermark embedding modification and propose the linear proportionality between MSE and the sum of energy of the selected wavelet coefficients for watermark embedding modification. The initial proposition assumes the orthonormality of discrete wavelet transform. It is further extended for non-orthonormal wavelet kernels using a weighting parameter that follows the energy conservation theorems in wavelet frames. The proposed analysis is verified by experimental results for both non-blind and blind watermarking schemes. Such a model is useful to find the optimum input parameters, including the wavelet kernel, coefficient selection, and subband choices for wavelet domain image watermarking.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2019 Association for Computing Machinery. This is an author-produced version of a paper subsequently published in ACM Transactions on Multimedia Computing, Communications and Applications. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | Watermarking; embedding distortion; wavelet; MSE |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Electronic and Electrical Engineering (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 17 Dec 2019 16:07 |
Last Modified: | 18 Dec 2019 09:55 |
Status: | Published |
Publisher: | Association for Computing Machinery (ACM) |
Refereed: | Yes |
Identification Number: | 10.1145/3357333 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:154715 |