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<p>Watermarking is a critical security concept and a challenging task when using medical images in healthcare, where it protects patient privacy. Medical images are frequently shared between hospitals and specialists for diagnosis and thus security is a key concern. A robust protection against transfer channel noise, including salt and pepper effects, accidental cropping, and unauthorized modifications, is required. This study presents a novel watermarking method for embedding imperceptible watermarks in clinical images to enhance data authenticity, integrity, and ownership verification. Our proposed technique combines Discrete Cosine Transform (DCT) and Discrete Wavelet Transform (DWT) techniques, which are more advanced traditional watermarking methods in offering improved image processing attack resistance with no compromise on the diagnostic quality of medical images. Another innovation in our method is the adaptive scaling factor, derived from the DWT-DCT coefficients, which varies dynamically with adjusted adjustments based on the significance of selected coefficients relative to the overall average. Utilizing this adaptive factor, our suggested method became a robust and flexible watermark embedding method, and thus, our suggested method became a robust and flexible watermark embedding method, thus, making it suitable for clinical imaging modalities. The proposed technique is designed to balance robustness, imperceptibility, and computational efficiency, making it well-suited for practical applications. To evaluate the efficacy of our watermarking technique, we have used Structural Similarity Index Measure (SSIM), Absolute Relative Error (ARE), and Peak Signal-to-Noise Ratio (PSNR) as key metrics. Experimental results show that our method achieves an SSIM of 1.000, PSNR of 49.11 dB, and ARE of 0.002, outperforming existing models and demonstrating exceptional capacity to maintain image integrity and safeguard sensitive medical information in digital environments. This research offers a high-performance, robust watermarking solution, advancing the security and confidentiality of digital medical data.</p>

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Discrete cosine transform and discrete wavelet transform based hybrid method for robust and blind medical image watermarking

  • 期刊论文

  • 发表日期：

    2025年7月21日

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  • Saima Kanwal,
  • Feng Tao,
  • Rizwan Taj,
  • Qamar Abbas,
  • Farhan Amin

摘要

Watermarking is a critical security concept and a challenging task when using medical images in healthcare, where it protects patient privacy. Medical images are frequently shared between hospitals and specialists for diagnosis and thus security is a key concern. A robust protection against transfer channel noise, including salt and pepper effects, accidental cropping, and unauthorized modifications, is required. This study presents a novel watermarking method for embedding imperceptible watermarks in clinical images to enhance data authenticity, integrity, and ownership verification. Our proposed technique combines Discrete Cosine Transform (DCT) and Discrete Wavelet Transform (DWT) techniques, which are more advanced traditional watermarking methods in offering improved image processing attack resistance with no compromise on the diagnostic quality of medical images. Another innovation in our method is the adaptive scaling factor, derived from the DWT-DCT coefficients, which varies dynamically with adjusted adjustments based on the significance of selected coefficients relative to the overall average. Utilizing this adaptive factor, our suggested method became a robust and flexible watermark embedding method, and thus, our suggested method became a robust and flexible watermark embedding method, thus, making it suitable for clinical imaging modalities. The proposed technique is designed to balance robustness, imperceptibility, and computational efficiency, making it well-suited for practical applications. To evaluate the efficacy of our watermarking technique, we have used Structural Similarity Index Measure (SSIM), Absolute Relative Error (ARE), and Peak Signal-to-Noise Ratio (PSNR) as key metrics. Experimental results show that our method achieves an SSIM of 1.000, PSNR of 49.11 dB, and ARE of 0.002, outperforming existing models and demonstrating exceptional capacity to maintain image integrity and safeguard sensitive medical information in digital environments. This research offers a high-performance, robust watermarking solution, advancing the security and confidentiality of digital medical data.