Optimal histogram-pair and prediction-error based reversible data hiding for medical images

Xuefeng Tong, Xin Wang, Guorong Xuan, Shumeng Li, Yun Q. Shi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations


In recent years, with the development of application research on medical images and medical documents, it is urgent to embed data, such as patient’s personal information, diagnostic information and verification information into medical images. Reversible data hiding for medical images is the technique of embedding medical data into medical images. However, most existed schemes of reversible data hiding for medical images could not achieve high performance and high payloads. This paper presents a reversible data hiding scheme for medical images based on histogram-pair and prediction-error. As the prediction-error histogram of medical images, compared with the gray level histogram of medical images, is more in line with quasi-Laplace distribution, histogram-pair and prediction-error based method could achieve high performance. We adjust the following four thresholds for optimal performance: embedding threshold, fluctuation threshold, left- and right-histogram shrinking thresholds. The left- and right-histogram shrinking thresholds are used not only to avoid underflow and/or overflow but also to achieve optimum performance. Compared to previous works, the proposed scheme has significant improvement in embedding capacity and marked image quality for medical images.

Original languageEnglish (US)
Title of host publicationDigital-Forensics and Watermarking - 14th International Workshop, IWDW 2015, Revised Selected Papers
EditorsIsao Echizen, Hyoung Joong Kim, Yun-Qing Shi, Fernando Pérez-González
PublisherSpringer Verlag
Number of pages14
ISBN (Print)9783319319599
StatePublished - 2016
Event14th International Workshop on Digital-Forensics and Watermarking, IWDW 2015 - Tokyo, Japan
Duration: Oct 7 2015Oct 10 2015

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other14th International Workshop on Digital-Forensics and Watermarking, IWDW 2015

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • General Computer Science


  • Histogram-pair
  • Medical image
  • Prediction-error
  • Reversible data hiding


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