Hierarchical watermarking framework based on analysis of local complexity variations

Hierarchical watermarking framework based on analysis of local complexity variations Multimed Tools Appl (2018) 77:30865–30890 https://doi.org/10.1007/s11042-018-6129-8 Hierarchical watermarking framework based on analysis of local complexity variations 1 2 3 Majid Mohrekesh & Shekoofeh Azizi & Shahram Shirani & 1 1,3 Nader Karimi & Shadrokh Samavi Received: 12 September 2017 /Revised: 2 May 2018 /Accepted: 9 May 2018 / Published online: 1 June 2018 Springer Science+Business Media, LLC, part of Springer Nature 2018 Abstract Increasing production and exchange of multimedia content have increased the need for better protection of copyright using watermarking. Different methods have been proposed to satisfy the tradeoff between imperceptibility and robustness as two important characteristics in watermarking while maintaining proper data-embedding capacity. Many watermarking methods use independent image set of parameters. Different images possess different poten- tials for the robust and transparent hosting of watermark data. To overcome this deficiency, in this paper we have proposed a new hierarchical adaptive watermarking framework. At the higher level of the hierarchy, the complexity of an image is ranked in comparison with complexities of images of a dataset. For a typical dataset of images, the statistical distribution of block complexities is found. At the lower level of the hierarchy, for a single cover image that is to be watermarked, http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Multimedia Tools and Applications Springer Journals

Hierarchical watermarking framework based on analysis of local complexity variations

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Publisher
Springer Journals
Copyright
Copyright © 2018 by Springer Science+Business Media, LLC, part of Springer Nature
Subject
Computer Science; Multimedia Information Systems; Computer Communication Networks; Data Structures, Cryptology and Information Theory; Special Purpose and Application-Based Systems
ISSN
1380-7501
eISSN
1573-7721
D.O.I.
10.1007/s11042-018-6129-8
Publisher site
See Article on Publisher Site

Abstract

Multimed Tools Appl (2018) 77:30865–30890 https://doi.org/10.1007/s11042-018-6129-8 Hierarchical watermarking framework based on analysis of local complexity variations 1 2 3 Majid Mohrekesh & Shekoofeh Azizi & Shahram Shirani & 1 1,3 Nader Karimi & Shadrokh Samavi Received: 12 September 2017 /Revised: 2 May 2018 /Accepted: 9 May 2018 / Published online: 1 June 2018 Springer Science+Business Media, LLC, part of Springer Nature 2018 Abstract Increasing production and exchange of multimedia content have increased the need for better protection of copyright using watermarking. Different methods have been proposed to satisfy the tradeoff between imperceptibility and robustness as two important characteristics in watermarking while maintaining proper data-embedding capacity. Many watermarking methods use independent image set of parameters. Different images possess different poten- tials for the robust and transparent hosting of watermark data. To overcome this deficiency, in this paper we have proposed a new hierarchical adaptive watermarking framework. At the higher level of the hierarchy, the complexity of an image is ranked in comparison with complexities of images of a dataset. For a typical dataset of images, the statistical distribution of block complexities is found. At the lower level of the hierarchy, for a single cover image that is to be watermarked,

Journal

Multimedia Tools and ApplicationsSpringer Journals

Published: Jun 1, 2018

References

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