Overlapping pixel value ordering predictor for high-capacity reversible data hiding

  • Chin-Feng Lee
  • Jau-Ji ShenEmail author
  • Yu-Chi Kao
  • Somya Agrawal
Special Issue Paper


In recent years, many reversible information hiding methods have been proposed. Among them, the pixel value ordering (PVO) method can be used to create high-fidelity camouflage images under good embedding capacity. The original PVO method adopted the block-by-block manner, and each block could embed only 2 bits. In this study, we propose an overlapping PVO (OPVO) method. In the PPVO method, secret data are embedded in the maximum and minimum pixel values to improve the situation in which only up to 1 bit can be embedded in a sliding window. In the pixel-by-pixel manner, each pixel can embed data multiple times. We make full use of the correlation between adjacent pixels in the natural image to increase the embedding capacity. An advantage of the overlapping PVO method is that its embedding capacity is more than twice as high as that of previous PVO series methods where an acceptable image quality is maintained. In our experiment, the embedding capacity of the smooth image is up to 130,000 bits, whereas that of the complex image is higher. However, the image quality decrease rate of the proposed method tends to be lower than that of the other methods. Therefore, any kind of image is suitable for our method.


Reversible data hiding (RDH) Difference expansion (DE) Histogram shifting (HS) Prediction-error expansion (PEE) Pixel-value-ordering (PVO) 



This research was partially supported by the Ministry of Science and Technology of the Republic of China under the Grants MOST 106-2221-E-324-006-MY2.


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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  • Chin-Feng Lee
    • 1
  • Jau-Ji Shen
    • 2
    Email author
  • Yu-Chi Kao
    • 2
  • Somya Agrawal
    • 1
  1. 1.Department of Information ManagementChaoyang University of TechnologyTaichungTaiwan
  2. 2.Department of Management Information SystemsNational Chung Hsing UniversityTaichungTaiwan

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