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Reversible Data Hiding Based on Partitioning the Prediction Values

  • Haihang Wu
  • Fangjun HuangEmail author
Conference paper
  • 41 Downloads
Part of the Lecture Notes in Computer Science book series (LNCS, volume 12022)

Abstract

In this paper, we present a new reversible data hiding (RDH) method. Instead of directly dividing the neighboring pixels into blocks, we sort the pixels according to their prediction values first, and then the sorted sequence is partitioned into non-overlapping blocks. That is, different from that in pixel value ordering (PVO) series only the neighboring pixels can be divided into the same block, in our new scheme the pixels far apart from each other in space may be divided into the same block in case they have the similar pixel values. Thus much redundancy in image can be exploited and a sharper prediction error histogram is easy to be obtained for data embedding. To achieve better performance, a new adaptive embedding strategy is also proposed. The experimental results show that our new method is superior to the traditional PVO based methods.

Keywords

Reversible data hiding Pixel value ordering Prediction value 

Notes

Acknowledgments

This work is partially supported by the National Natural Science Foundation of China (61772572), the NSFC-NRF Scientific Cooperation Program (61811540409), and the Natural Science Foundation of Guangdong Province of China (2017A030313366).

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Guangdong Provincial Key Laboratory of Information Security Technology, School of Data and Computer ScienceSun Yat-Sen UniversityGuangzhouChina

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