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1st International Conference on Industrial Networks and Intelligent Systems

Research Article

Reversible and Embedded Watermarking of Medical Images for Telemedicine

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  • @INPROCEEDINGS{10.4108/icst.iniscom.2015.258307,
        author={Chung-Yen Su and Jeng-Ji Huang and Che-Yang Shih and Yu-Tang Chen},
        title={Reversible and Embedded Watermarking of Medical Images for Telemedicine},
        proceedings={1st International Conference on Industrial Networks and Intelligent Systems},
        publisher={EAI},
        proceedings_a={INISCOM},
        year={2015},
        month={4},
        keywords={integer wavelet transform; lossless compression; reversible watermarking; spiht},
        doi={10.4108/icst.iniscom.2015.258307}
    }
    
  • Chung-Yen Su
    Jeng-Ji Huang
    Che-Yang Shih
    Yu-Tang Chen
    Year: 2015
    Reversible and Embedded Watermarking of Medical Images for Telemedicine
    INISCOM
    ICST
    DOI: 10.4108/icst.iniscom.2015.258307
Chung-Yen Su1,*, Jeng-Ji Huang1, Che-Yang Shih1, Yu-Tang Chen1
  • 1: Department of Electrical Engineering, National Taiwan Normal University
*Contact email: scy@ntnu.edu.tw

Abstract

In this paper, we propose a new reversible watermarking of medical images for the applications in telemedicine. By using a bit-stream insertion scheme, the patient’s information can be treated as a watermark and can be embedded into the bit-stream of a cover image for remote transmission. The proposed method simplifies the design of traditional image coding after a reversible watermarking. Experimental results show that the compression ratio can be achieved up to 3.025. The watermarking capacity can be obtained over 0.75 bpp for some common images. In addition, the watermark can be extracted exactly and the cover image can be reconstructed either in a lossless way or a lossy way. The obtained results also show the improvement with respect to previous works.

Keywords
integer wavelet transform; lossless compression; reversible watermarking; spiht
Published
2015-04-09
Publisher
EAI
http://dx.doi.org/10.4108/icst.iniscom.2015.258307
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