Optimal histogram-pair and prediction-error based reversible data hiding for medical images

Document Type

Article

Publication Date

1-1-2016

Abstract

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.

Identifier

84964043878 (Scopus)

ISBN

[9783319319599]

Publication Title

Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics

External Full Text Location

https://doi.org/10.1007/978-3-319-31960-5_31

e-ISSN

16113349

ISSN

03029743

First Page

378

Last Page

391

Volume

9569

Grant

12ZZ033

Fund Ref

National Natural Science Foundation of China

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