TY - JOUR
T1 - Skewed Histogram Shifting for Reversible Data Hiding Using a Pair of Extreme Predictions
AU - Kim, Suah
AU - Qu, Xiaochao
AU - Sachnev, Vasily
AU - Kim, Hyoung Joong
N1 - Funding Information:
Manuscript received December 22, 2016; revised August 8, 2017, June 26, 2018, August 8, 2018, and September 3, 2018; accepted October 23, 2018. Date of publication October 31, 2018; date of current version October 29, 2019. This work was supported in part by the Institute for Information and Communications Technology Promotion (IITP) grant through the Korean Government (MSIP) (development of on–off hybrid blockchain technology for real-time large-scale data distribution) under Grant 2018-0-00365, and in part by the Framework of International Cooperation Program managed by the National Research Foundation of Korea under Grant 2018K2A9A2A06024168, FY2018. This paper was recommended by Associate Editor G. Hua. (Corresponding author: Hyoung Joong Kim.) S. Kim and H. J. Kim are with the Graduate School of Information Security, Korea University, Seoul 02841, South Korea (e-mail: suahnkim@gmail.com; khj-@korea.ac.kr).
Publisher Copyright:
© 2018 IEEE.
PY - 2019/11
Y1 - 2019/11
N2 - Reversible data hiding hides data in an image such that the original image is recoverable. This paper presents a novel embedding framework with reduced distortion called skewed histogram shifting using a pair of extreme predictions. Unlike traditional prediction error histogram shifting schemes, where only one good prediction is used to generate a prediction error histogram, the proposed scheme uses a pair of extreme predictions to generate two skewed histograms. By exploiting the structure of the skewed histogram, only the pixels from the peak and the short tail are used for embedding, which decreases the distortion from the lesser number of pixels being shifted. Detailed experiments and analysis are provided using several image databases.
AB - Reversible data hiding hides data in an image such that the original image is recoverable. This paper presents a novel embedding framework with reduced distortion called skewed histogram shifting using a pair of extreme predictions. Unlike traditional prediction error histogram shifting schemes, where only one good prediction is used to generate a prediction error histogram, the proposed scheme uses a pair of extreme predictions to generate two skewed histograms. By exploiting the structure of the skewed histogram, only the pixels from the peak and the short tail are used for embedding, which decreases the distortion from the lesser number of pixels being shifted. Detailed experiments and analysis are provided using several image databases.
KW - Reversible data hiding
KW - reversible watermarking
KW - skewed histogram shifting
UR - http://www.scopus.com/inward/record.url?scp=85055865813&partnerID=8YFLogxK
U2 - 10.1109/TCSVT.2018.2878932
DO - 10.1109/TCSVT.2018.2878932
M3 - Article
AN - SCOPUS:85055865813
VL - 29
SP - 3236
EP - 3246
JO - IEEE Transactions on Circuits and Systems for Video Technology
JF - IEEE Transactions on Circuits and Systems for Video Technology
SN - 1051-8215
IS - 11
M1 - 8517133
ER -