TY - GEN
T1 - Optimal histogram-pair and prediction-error based reversible data hiding for medical images
AU - Tong, Xuefeng
AU - Wang, Xin
AU - Xuan, Guorong
AU - Li, Shumeng
AU - Shi, Yun Q.
N1 - Publisher Copyright:
© Springer International Publishing Switzerland 2016.
PY - 2016
Y1 - 2016
N2 - In recent years, with the development of application research on medical images and medical documents, it is urgent to embed data, such as patient’s personal information, diagnostic information and verification information into medical images. Reversible data hiding for medical images is the technique of embedding medical data into medical images. However, most existed schemes of reversible data hiding for medical images could not achieve high performance and high payloads. This paper presents a reversible data hiding scheme for medical images based on histogram-pair and prediction-error. As the prediction-error histogram of medical images, compared with the gray level histogram of medical images, is more in line with quasi-Laplace distribution, histogram-pair and prediction-error based method could achieve high performance. We adjust the following four thresholds for optimal performance: embedding threshold, fluctuation threshold, left- and right-histogram shrinking thresholds. The left- and right-histogram shrinking thresholds are used not only to avoid underflow and/or overflow but also to achieve optimum performance. Compared to previous works, the proposed scheme has significant improvement in embedding capacity and marked image quality for medical images.
AB - In recent years, with the development of application research on medical images and medical documents, it is urgent to embed data, such as patient’s personal information, diagnostic information and verification information into medical images. Reversible data hiding for medical images is the technique of embedding medical data into medical images. However, most existed schemes of reversible data hiding for medical images could not achieve high performance and high payloads. This paper presents a reversible data hiding scheme for medical images based on histogram-pair and prediction-error. As the prediction-error histogram of medical images, compared with the gray level histogram of medical images, is more in line with quasi-Laplace distribution, histogram-pair and prediction-error based method could achieve high performance. We adjust the following four thresholds for optimal performance: embedding threshold, fluctuation threshold, left- and right-histogram shrinking thresholds. The left- and right-histogram shrinking thresholds are used not only to avoid underflow and/or overflow but also to achieve optimum performance. Compared to previous works, the proposed scheme has significant improvement in embedding capacity and marked image quality for medical images.
KW - Histogram-pair
KW - Medical image
KW - Prediction-error
KW - Reversible data hiding
UR - http://www.scopus.com/inward/record.url?scp=84964043878&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84964043878&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-31960-5_31
DO - 10.1007/978-3-319-31960-5_31
M3 - Conference contribution
AN - SCOPUS:84964043878
SN - 9783319319599
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 378
EP - 391
BT - Digital-Forensics and Watermarking - 14th International Workshop, IWDW 2015, Revised Selected Papers
A2 - Echizen, Isao
A2 - Kim, Hyoung Joong
A2 - Shi, Yun-Qing
A2 - Pérez-González, Fernando
PB - Springer Verlag
T2 - 14th International Workshop on Digital-Forensics and Watermarking, IWDW 2015
Y2 - 7 October 2015 through 10 October 2015
ER -