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Pixel-Value-Ordering Based Reversible Data Hiding with Adaptive Texture Classification and Modification

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Digital Forensics and Watermarking (IWDW 2018)

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 11378))

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Abstract

Pixel-value-ordering (PVO) is a new technique for the high-fidelity reversible data hiding (RDH). It contains a process of sorting the pixels of a block by their values at first and then embedding into data bits into the maximum or minimum pixels of a block. In this paper, we propose to modify the pixel blocks differently according to how smooth they are, and embed the adequate number of bits into different types of blocks. The pixel blocks are first classified into five types based on the local complexity. The maximum pixels of the most smooth block will be embedded at most four bits, and the less smooth ones are embedded with a lower number of bits. The block classification is dynamically adjusted to achieve the adaptive embedding with the best trade-off between the capacity and the embedding distortion. Experimental results show that the proposed method can give a better performance over the previous PVO-based methods.

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Acknowledgement

This work was supported by the National Science Foundation of China (No. 61502160), the Hunan Provincial Natural Science Foundation of China under grant No. 2018JJ3078 and the Fundamental Research Funds for the Central Universities.

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Authors and Affiliations

  1. College of Computer Science and Electronic Engineering, Hunan University, Changsha, 410082, China

    Bo Ou

  2. Institute of Information Science, Beijing Jiaotong University, Beijing, 100044, China

    Xiaolong Li

  3. School of Mathematical Sciences, Capital Normal University, Beijing, 100048, China

    Wei Li

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

    Yun-Qing Shi

Authors
  1. Bo Ou
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  2. Xiaolong Li
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  3. Wei Li
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  4. Yun-Qing Shi
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Corresponding author

Correspondence to Bo Ou .

Editor information

Editors and Affiliations

  1. Korea Advanced Institute of Science and Technology, Daejeon, Korea (Republic of)

    Chang D. Yoo

  2. New Jersey Institute of Technology, Newark, NJ, USA

    Yun-Qing Shi

  3. Korea University, Seoul, Korea (Republic of)

    Hyoung Joong Kim

  4. University of Florence, Florence, Italy

    Alessandro Piva

  5. Korea Advanced Institute of Science and Technology, Daejeon, Korea (Republic of)

    Gwangsu Kim

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Ou, B., Li, X., Li, W., Shi, YQ. (2019). Pixel-Value-Ordering Based Reversible Data Hiding with Adaptive Texture Classification and Modification. In: Yoo, C., Shi, YQ., Kim, H., Piva, A., Kim, G. (eds) Digital Forensics and Watermarking. IWDW 2018. Lecture Notes in Computer Science(), vol 11378. Springer, Cham. https://doi.org/10.1007/978-3-030-11389-6_13

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  • DOI: https://doi.org/10.1007/978-3-030-11389-6_13

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-11388-9

  • Online ISBN: 978-3-030-11389-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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