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A robust blind medical image watermarking approach for telemedicine applications
- Source :
- Cluster Computing
- Publication Year :
- 2021
- Publisher :
- Springer US, 2021.
-
Abstract
- In order to enhance the security of exchanged medical images in telemedicine, we propose in this paper a blind and robust approach for medical image protection. This approach consists in embedding patient information and image acquisition data in the image. This imperceptible integration must generate the least possible distortion. The watermarked image must present the same clinical reading as the original image. The proposed approach is applied in the frequency domain. For this purpose, four transforms were used: discrete wavelets transform, non-subsampled contourlet transform, non-subsampled shearlet transform and discreet cosine transform. All these transforms was combined with Schur decomposition and the watermark bits were integrated in the upper triangular matrix. To obtain a satisfactory compromise between robustness and imperceptibility, the integration was performed in the medium frequencies of the image. Imperceptibility and robustness experimental results shows that the proposed methods maintain a high quality of watermarked images and are remarkably robust against several conventional attacks.
- Subjects :
- Discrete wavelet transform
Computer Networks and Communications
Computer science
Data_MISCELLANEOUS
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
02 engineering and technology
Article
Wavelet
Non-subsampled contourlet transform
Robustness (computer science)
Distortion
0202 electrical engineering, electronic engineering, information engineering
Discrete cosine transform
Computer vision
Digital watermarking
Non-subsampled shearlet transform
Discreet cosine transform
business.industry
020206 networking & telecommunications
Watermark
Contourlet
Medical image
Schur decomposition
Frequency domain
020201 artificial intelligence & image processing
Artificial intelligence
business
Software
Subjects
Details
- Language :
- English
- ISSN :
- 15737543 and 13867857
- Database :
- OpenAIRE
- Journal :
- Cluster Computing
- Accession number :
- edsair.doi.dedup.....fe176ae2a3b59aedcd91004d50f45594