Abstract—Reversible data hiding can recover the original
image from the marked image without any distortion. This
paper presents a novel prediction error based reversible data
hiding method using histogram shifting in spatial domain.
Three predictors including Mean, JPEG lossless and median
edge detector (MED) are employed to compute prediction
values for current pixels, respectively. Prediction errors are
calculated as well to build histogram bins. Histogram shifting
mechanism is designed that bins with large prediction errors
are shifted based on hiding level, and thus, it will not hurt
marked image if hiding level is not high. Histogram bins with
small error predictions are used to hide secret data.
Experimental results demonstrate that average of prediction
error is less than that of interpolation error used in existing
data hiding methods, and the proposed method is good at high
capacity hiding. MED is the best predictor among three
predictors in the proposed method, and it outperforms existing
data hiding methods in terms of capacity and marked image
quality.
Index Terms—Reversible data hiding, histogram shifting,
median edge detector, prediction error.
Ting Luo and Gao Wei are with the Faculty of Information Science and
Engineering, Ningbo University, Ningbo 315211 China (e-mail: luoting@
nbu.edu.cn, gaowei@nbu.edu.cn).
Gangyi Jiang and Mei Yu are with the Faculty of Information Science and
Engineering, Ningbo University, Ningbo 315211 China; they are also with
the National Key Lab of Software New Technology, Nanjing University,
Nanjing 210093, China (e-mail: jianggangyi@126.com, yumei2@126.com).
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Cite:Ting Luo, Gangyi Jiang, Mei Yu, and Wei Gao, "Novel Prediction Error Based Reversible Data Hiding Method Using Histogram Shifting," International Journal of Computer Theory and Engineering vol. 7, no. 5, pp. 332-336, 2015.
