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Image Quality Assessment in Reversible Data Hiding with Contrast Enhancement

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Digital Forensics and Watermarking (IWDW 2017)

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 10431))

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Abstract

In this paper, image quality assessment (IQA) in reversible data hiding with contrast enhancement (RDH-CE) is studied. Firstly, the schemes of RDH-CE are reviewed, with which image contrast can be enhanced without any information loss. Secondly, the limitations of using the peak signal-to-noise ratio (PSNR) to indicate image quality in the scenario of RDH-CE are discussed. Subsequently, three no-reference IQA metrics and four metrics specially designed for contrast-changed images are adopted, in addition to PSNR and structural similarity (SSIM) index. By using these metrics, the evaluation results on the contrast-enhanced images generated with two RDH-CE schemes are obtained and compared. The experimental results have shown that the no-reference IQA metrics, the blind/referenceless image spatial quality evaluator (BRISQUE) for instance, are more suitable than PSNR and SSIM index for the images that have been enhanced by the RDH-CE schemes. Furthermore, how to use the suitable IQA metrics has been discussed for performance evaluation of RDH-CE schemes.

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Acknowledgment

This work was supported by National Natural Science Foundation of China (No. 61632013), Natural Science Foundation of Jiangsu Province of China (No. BK20151131), Guangdong Provincial Natural Science Foundation of China (No. 2014A030308006), Guangdong Provincial Project of Science and Technology of China (No. 2016B090920081), and SCUT Fundamental Research Funds for the Central Universities of China (No. 2017MS038).

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Authors and Affiliations

  1. School of Computer Science and Engineering, South China University of Technology, Guangzhou, 510006, People’s Republic of China

    Hao-Tian Wu & Shaohua Tang

  2. Department of Electrical and Computer Engineering, New Jersey Institute of Technology, Newark, NJ, 07103, USA

    Yun-Qing Shi

Authors
  1. Hao-Tian Wu
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  2. Shaohua Tang
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  3. Yun-Qing Shi
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Corresponding author

Correspondence to Hao-Tian Wu .

Editor information

Editors and Affiliations

  1. Department of Computer Science, Otto-von-Guericke University Magdeburg, Magdeburg, Germany

    Christian Kraetzer

  2. Department of Electrical and Computer Engineering, New Jersey Institute of Technology, Newark, New Jersey, USA

    Yun-Qing Shi

  3. Department of Computer Science, Otto-von-Guericke University Magdeburg, Magdeburg, Germany

    Jana Dittmann

  4. Graduate School Information Security, Korea University, Seoul, Korea (Republic of)

    Hyoung Joong Kim

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Wu, HT., Tang, S., Shi, YQ. (2017). Image Quality Assessment in Reversible Data Hiding with Contrast Enhancement. In: Kraetzer, C., Shi, YQ., Dittmann, J., Kim, H. (eds) Digital Forensics and Watermarking. IWDW 2017. Lecture Notes in Computer Science(), vol 10431. Springer, Cham. https://doi.org/10.1007/978-3-319-64185-0_22

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  • DOI: https://doi.org/10.1007/978-3-319-64185-0_22

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-64184-3

  • Online ISBN: 978-3-319-64185-0

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