A Novel Texture-Quantization-Based Reversible Multiple Watermarking Scheme Applied to Health Information System.

Area of Science:

• Medical Imaging
• Information Security
• Digital Watermarking

Background:

• Innovations in information and communication technologies have transformed health information systems (HIS).
• Advances in HIS increase medical image security concerns regarding confidentiality, reliability, and integrity.
• Digital watermarking offers solutions for HIS security, but texture features remain underexplored for robustness.

Purpose of the Study:

• To present a novel hybrid texture-quantization-based approach for reversible multiple watermarking in HIS.
• To exploit image texture properties for improved robustness in digital watermarking.
• To enhance the security and integrity of medical images within health information systems.

Main Methods:

• Developed a hybrid texture-quantization method for reversible multiple watermarking.
• Employed texture properties for detecting embedding sites to improve watermarking robustness.
• Integrated BCH encoded watermarks and ADM encrypted ECG signals for enhanced security.

Main Results:

• Achieved superior watermarked image quality, validated by PSNR, SSIM, and UIQI, outperforming state-of-the-art methods.
• Demonstrated robustness against various image processing attacks, including JPEG compression, across multiple medical imaging modalities (CT, MRA, MRI, US).
• Attained a maximum data hiding capacity of 22,616 bits with a PSNR of 53.64 dB.

Conclusions:

• The proposed texture-quantization watermarking scheme significantly enhances medical image security and robustness in HIS.
• The method offers a promising solution for protecting sensitive medical data while maintaining high image quality.
• This approach represents a notable advancement in reversible multiple watermarking for healthcare applications.