Analysis of DWT–DCT watermarking algorithm on digital medical imaging

Rajkumar Soundrapandiyan; Kannadasan Rajendiran; Arunkumar Gurunathan; Akila Victor; Ramani Selvanambi

doi:10.1117/1.JMI.11.1.014002

28 December 2023 Analysis of DWT–DCT watermarking algorithm on digital medical imaging

Rajkumar Soundrapandiyan, Kannadasan Rajendiran, Arunkumar Gurunathan, Akila Victor, Ramani Selvanambi

Author Affiliations +

Journal of Medical Imaging, Vol. 11, Issue 1, 014002 (December 2023). https://doi.org/10.1117/1.JMI.11.1.014002

Abstract

Purpose

Over the past decade, the diagnostic information of the patients are digitally recorded and transferred. During the transmission of patients data, the security and authenticity of the information has to be ensured. Medical image watermarking technology has recently advanced because it can be used to conceal patient information while ensuring the authenticity. We propose a multiple watermarking method for securing clinical medical images.

Approach

In this watermarking method, the quality feature property and private label property information are embedded as watermarks in the original image. Initially, medical images are divided into the region of interest (ROI) and non-interest region (NIR). Second, a two-level discrete wavelet transform (DWT) is applied to the ROI and the coefficients LL1 (LL2, LH2, HL2, HH2), LH1, HL1, and HH1 are generated. Watermarks are embedded using the DWT low-frequency sub-band (LL2) by quantizing the low-frequency coefficients. Next, the NIR is separated into non-overlapping 8×8 blocks, and a discrete cosine transform (DCT) is applied for each block. The DCT coefficients of each block are sorted using the zigzag transform. For embedding, eight intermediate frequency coefficients are used. Finally, the feature information is embedded in the ROI, and the tag information is embedded in the NIR.

Results

The performance of the DWT-DCT watermarking method is calculated using the metrics of peak signal-to-noise ratio (PSNR), structural similarity index measure, and mean square error. The proposed method obtained the better PSNR value of 45.76 dB.

Conclusions

The proposed model works well for clinical medical images when compared with the existing techniques.

Citation Download Citation

Rajkumar Soundrapandiyan, Kannadasan Rajendiran, Arunkumar Gurunathan, Akila Victor, and Ramani Selvanambi "Analysis of DWT–DCT watermarking algorithm on digital medical imaging," Journal of Medical Imaging 11(1), 014002 (28 December 2023). https://doi.org/10.1117/1.JMI.11.1.014002

Received: 24 December 2022; Accepted: 11 December 2023; Published: 28 December 2023

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KEYWORDS

Digital watermarking

Near infrared

Medical imaging

Discrete wavelet transforms

Image encryption

Image processing

Quantization

Purpose

Approach

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Conclusions

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