NDLI: Double-threshold reversible data hiding

Content Provider	IEEE Xplore Digital Library
Author	Guorong Xuan Shi, Y.Q. Jianzhong Teng Xuefeng Tong Peiqi Chai
Copyright Year	2010
Description	Author affiliation: Dept. of Computer Science, Tongji University, Shanghai, China (Guorong Xuan; Jianzhong Teng; Xuefeng Tong; Peiqi Chai) \|\| Dept. of ECE, New Jersey Institute of Technology, Newark, New Jersey, USA (Shi, Y.Q.)
Abstract	This proposed scheme reversibly embeds data into image prediction-errors by using histogram-pair method with double thresholds (embedding threshold and fluctuation threshold). The embedding threshold is used to select only those prediction-errors, whose magnitude does not exceed this threshold, for possible reversible data hiding. The fluctuation threshold is used to select only those prediction-errors, whose associated neighbor fluctuation does not exceed this threshold, for possible reversible data hiding. Only when both thresholds are satisfied the reversible data hiding is carried out. Image gray level histogram modification is conducted to shrink the image histogram towards the center to avoid underflow and/or overflow only when this is necessary. The required bookkeeping data are embedded together with pure payload for original image recovery late. The experimental results have demonstrated that the proposed scheme outperforms recently published reversible image data hiding schemes in terms of the highest PSNR of marked image vs. original image at given pure payloads.
Starting Page	1129
Ending Page	1132
File Size	428078
Page Count	4
File Format	PDF
ISBN	9781424453085
DOI	10.1109/ISCAS.2010.5537323
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-05-30
Publisher Place	France
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Data encapsulation Fluctuations Histograms Payloads Pixel Data mining Discrete wavelet transforms Computer science PSNR Authentication gray level histogram modification reversible image data hiding prediction error neighborhood fluctuation histogram pair scheme
Content Type	Text
Resource Type	Article

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