Signal, Image and Video Processing

, Volume 7, Issue 2, pp 297–306 | Cite as

High performance reversible data hiding for block truncation coding compressed images

  • Wei Sun
  • Zhe-Ming LuEmail author
  • Yu-Chun Wen
  • Fa-Xin Yu
  • Rong-Jun Shen
Original Paper


Reversible data hiding has been a hot research topic because it can recover both the host media and hidden data without distortion. Because most digital images are stored and transmitted in compressed forms, such as JPEG, vector quantization, and block truncation coding (BTC), the reversible data hiding schemes in compressed domains have been paid more and more attention. Compared with transform coding, BTC has a significantly low complexity and less memory requirement, it therefore becomes an ideal data hiding domain. Traditional data hiding schemes in the BTC domain modify the BTC encoding stage or BTC-compressed data according to the secret bits, and they have a relatively low efficiency and meanwhile may reduce the image quality. This paper presents a novel reversible data hiding scheme based on the joint neighbor coding technique for BTC-compressed images by further losslessly encoding the BTC-compressed data according to the secret bits. First, BTC is performed on the original image to obtain the BTC-compressed data that can be represented by a high mean table, a low mean table, and a bitplane sequence. Then, the secret data are losslessly embedded in both the high mean and low mean tables. Our hiding scheme is a lossless method based on the relation among the current value and the neighboring ones in mean tables. In addition, it can averagely embed 2 bits in each mean value, which increases the capacity and efficiency. Experimental results show that our scheme outperforms three existing BTC-based data hiding works, in terms of the bit rate, capacity, and efficiency.


Data hiding Reversible data hiding Joint neighbor coding Block truncation coding 

List of symbols


The image width


The block width


The image height


The block height


The initial reference location for encoding I cur, h cur and l cur


The offset of the reference index used to encode I cur


The offset of the reference high mean for encoding h cur

\({b_{o}^{(L) }}\)

The offset of the reference low mean for encoding l cur


The codestream of bitplane


The final location of the reference index to encode I cur


The final location of the reference high mean for encoding h cur


The final location of the reference low mean for encoding l cur


The codestream of the embedded high mean table


The codestream of the embedded low mean table


The difference between I cur and I ref


The difference between h cur and h ref


The difference between l cur and l ref


The m bits binary code of D


The high mean table

hij, 1 ≤ iA/a, 1 ≤ jB/b

The high mean of block x (ij)


The current high mean to be encoded


The reference high mean used to encode h cur


The current index to be encoded


The reference index used to encode I cur

lij, 1 ≤ iA/a, 1 ≤ jB/b

The low mean of block x (ij)


The low mean table


The codestream length


The current low mean to be encoded


The reference low mean used to encode l cur


The truncation integer used to distinguish the range of D, D H , and D L


The VQ codebook size


The number of neighboring indices considered


The bitplane sequence

pij, 1 ≤ iA/a, 1 ≤ jB/b

The bitplane of block x (ij)

tij, 1 ≤ iA/a, 1 ≤ jB/b

The mean value of block x (ij)


The original image

\({\left\lceil x \right\rceil}\)

The least integer not less than x

x(ij), 1 ≤ iA/a, 1 ≤ jB/b

The image block in the i-th row and j-th column

\({x_{uv}^{(ij)},\; 1\leq u \leq a, 1 \leq v \leq b}\)

The pixel at the location (u, v) of block x (ij)


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Copyright information

© Springer-Verlag London Limited 2011

Authors and Affiliations

  • Wei Sun
    • 1
  • Zhe-Ming Lu
    • 1
    Email author
  • Yu-Chun Wen
    • 1
  • Fa-Xin Yu
    • 1
  • Rong-Jun Shen
    • 1
  1. 1.School of Aeronautics and AstronauticsZhejiang UniversityHangzhouPeople’s Republic of China

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