Multimedia Tools and Applications

, Volume 77, Issue 20, pp 26711–26739 | Cite as

An improved reversible data hiding scheme using best neighboring coding based on color images

  • Lingfei WangEmail author
  • Zhibin PanEmail author


In this paper, an improved reversible data hiding (RDH) scheme, best neighboring coding (BNC), is proposed for vector quantization (VQ) compressed color images. As a result, it improves joint neighboring coding (JNC) based schemes, which take advantage of correlation between indices to embed secret bits (SB) and achieves good compression rate. As the correlation between RGB channels and the information of reference channel are employed, the best neighboring blocks of the other channels are obtained. The experimental results indicate that BNC enhances the prediction possibility of the best neighboring index by about 2.5 times compared to the conventional JNC method, which applies the current index and one of its four neighbor indices pointed by the secret data to generate the difference. Consequently, a more concentrated distribution of difference between current index and its neighboring index is obtained. After encoding this distribution generated by RGB channels, better compression rate and higher embedding efficiency are derived. Furthermore, extended experiments demonstrate that the proposed method outperforms other state-of-the-art RDH methods as well.


Reversible data hiding (RDH) Vector quantization (VQ) Compression domain Color channels correlation Joint neighboring coding (JNC) Best neighboring coding (BNC) 



This work is supported in part by the Open Research Fund of Key Laboratory of Spectral Imaging Technology, Chinese Academy of Sciences (Grant No. LSIT201606D), the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD), the Open Project Program of the State Key Lab of Novel Software Technology (Grant No. KFKT2016B14), Nanjing University and the Industrial Program of Zhejiang Province (Grant No. 2016C31090).


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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.School of Electronic and Information EngineeringXi’an Jiaotong UniversityXi’anPeople’s Republic of China
  2. 2.State Key Laboratory for Novel Software TechnologyNanjing UniversityNanjingPeople’s Republic of China

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