Lossless data embedding--new paradigm in digital watermarking
EURASIP Journal on Applied Signal Processing - Emerging applications of multimedia data hiding
A virtual image cryptosystem based upon vector quantization
IEEE Transactions on Image Processing
Reversible data embedding using a difference expansion
IEEE Transactions on Circuits and Systems for Video Technology
Embedding capacity raising in reversible data hiding based on prediction of difference expansion
Journal of Systems and Software
Reversible data hiding based on block median preservation
Information Sciences: an International Journal
Medical image security and EPR hiding using Shamir's secret sharing scheme
Journal of Systems and Software
Reversible data-hiding for progressive image transmission
Image Communication
A reversible data hiding method by histogram shifting in high quality medical images
Journal of Systems and Software
An efficient and secure medical image protection scheme based on chaotic maps
Computers in Biology and Medicine
Multimedia Tools and Applications
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Nowadays, the transmission of digitized medical information has become very convenient due to the generality of Internet. Regardless of the prevention of medical fault, the real-time detection of abnormal event, the support of clinical decision, even the model developing of medical service based on patient, Internet has created the biggest benefit to achieve the goals of promoting patient safety and medicine quality. However, it is easier that the hackers can grab or duplicate the digitized information on the Internet. This will cause following problems of medical security and copyright protection. Therefore, the information hiding techniques are developed for protection of medical information and copyright. This paper proposes a multiple-layer data hiding technique in spatial domain. It utilizes a reduced difference expansion method to embed the bitstream in the least significant bits (LSBs) of the expanded differences. By using the reduced difference expansion method, we can embed a large amount of data in a medical image whose quality can also be maintained. Moreover, the original image can be restored after extracting the hidden data from the stego-image. Experimental results show that the proposed scheme provides higher embedding capacity at the same level image quality compared with Tian's difference expansion method.