A robust blind medical image watermarking approach for telemedicine applications
| Autor: | Redouane Kafi, Fares Kahlessenane, Amine Khaldi, Salah Euschi |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
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 |
| Zdroj: | Cluster Computing |
| ISSN: | 1573-7543 1386-7857 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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