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Multiple Perspective of Multipredictor Mechanism and Multihistogram Modification for High-Fidelity Reversible Data Hiding.

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Title: Multiple Perspective of Multipredictor Mechanism and Multihistogram Modification for High-Fidelity Reversible Data Hiding.
Authors: Kai Gao1, Chin-Chen Chang1 alan3c@gmail.com, Chia-Chen Lin2 ally.cclin@ncut.edu.tw
Source: Computer Systems Science & Engineering. 2024, Vol. 48 Issue 3, p813-833. 21p.
Subjects: Reversible data hiding (Computer science), Prediction models, Histograms, Knapsack problems, Confidential communications, Image files, Image quality in imaging systems, Embeddings (Mathematics)
Abstract: Reversible data hiding is a confidential communication technique that takes advantage of image file characteristics, which allows us to hide sensitive data in image files. In this paper, we propose a novel high-fidelity reversible data hiding scheme. Based on the advantage of the multipredictor mechanism, we combine two effective prediction schemes to improve prediction accuracy. In addition, the multihistogram technique is utilized to further improve the image quality of the stego image. Moreover, a model of the grouped knapsack problem is used to speed up the search for the suitable embedding bin in each sub-histogram. Experimental results show that the quality of the stego image of our scheme outperforms state-of-the-art schemes in most cases. [ABSTRACT FROM AUTHOR]
Copyright of Computer Systems Science & Engineering is the property of Tech Science Press and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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Header DbId: egs
DbLabel: Engineering Source
An: 177472548
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
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  Data: Multiple Perspective of Multipredictor Mechanism and Multihistogram Modification for High-Fidelity Reversible Data Hiding.
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  Data: <searchLink fieldCode="AR" term="%22Kai+Gao%22">Kai Gao</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Chin-Chen+Chang%22">Chin-Chen Chang</searchLink><relatesTo>1</relatesTo><i> alan3c@gmail.com</i><br /><searchLink fieldCode="AR" term="%22Chia-Chen+Lin%22">Chia-Chen Lin</searchLink><relatesTo>2</relatesTo><i> ally.cclin@ncut.edu.tw</i>
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  Data: <searchLink fieldCode="JN" term="%22Computer+Systems+Science+%26+Engineering%22">Computer Systems Science & Engineering</searchLink>. 2024, Vol. 48 Issue 3, p813-833. 21p.
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  Data: <searchLink fieldCode="DE" term="%22Reversible+data+hiding+%28Computer+science%29%22">Reversible data hiding (Computer science)</searchLink><br /><searchLink fieldCode="DE" term="%22Prediction+models%22">Prediction models</searchLink><br /><searchLink fieldCode="DE" term="%22Histograms%22">Histograms</searchLink><br /><searchLink fieldCode="DE" term="%22Knapsack+problems%22">Knapsack problems</searchLink><br /><searchLink fieldCode="DE" term="%22Confidential+communications%22">Confidential communications</searchLink><br /><searchLink fieldCode="DE" term="%22Image+files%22">Image files</searchLink><br /><searchLink fieldCode="DE" term="%22Image+quality+in+imaging+systems%22">Image quality in imaging systems</searchLink><br /><searchLink fieldCode="DE" term="%22Embeddings+%28Mathematics%29%22">Embeddings (Mathematics)</searchLink>
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  Label: Abstract
  Group: Ab
  Data: Reversible data hiding is a confidential communication technique that takes advantage of image file characteristics, which allows us to hide sensitive data in image files. In this paper, we propose a novel high-fidelity reversible data hiding scheme. Based on the advantage of the multipredictor mechanism, we combine two effective prediction schemes to improve prediction accuracy. In addition, the multihistogram technique is utilized to further improve the image quality of the stego image. Moreover, a model of the grouped knapsack problem is used to speed up the search for the suitable embedding bin in each sub-histogram. Experimental results show that the quality of the stego image of our scheme outperforms state-of-the-art schemes in most cases. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Computer Systems Science & Engineering is the property of Tech Science Press and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.32604/csse.2024.038308
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 21
        StartPage: 813
    Subjects:
      – SubjectFull: Reversible data hiding (Computer science)
        Type: general
      – SubjectFull: Prediction models
        Type: general
      – SubjectFull: Histograms
        Type: general
      – SubjectFull: Knapsack problems
        Type: general
      – SubjectFull: Confidential communications
        Type: general
      – SubjectFull: Image files
        Type: general
      – SubjectFull: Image quality in imaging systems
        Type: general
      – SubjectFull: Embeddings (Mathematics)
        Type: general
    Titles:
      – TitleFull: Multiple Perspective of Multipredictor Mechanism and Multihistogram Modification for High-Fidelity Reversible Data Hiding.
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            NameFull: Kai Gao
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            NameFull: Chin-Chen Chang
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            NameFull: Chia-Chen Lin
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          Dates:
            – D: 01
              M: 03
              Text: 2024
              Type: published
              Y: 2024
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              Value: 48
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            – TitleFull: Computer Systems Science & Engineering
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