Analysis of DWT-DCT watermarking algorithm on digital medical imaging

J Med Imaging (Bellingham). 2024 Jan;11(1):014002. doi: 10.1117/1.JMI.11.1.014002. Epub 2023 Dec 28.

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.

Keywords: Arnold transform; discrete cosine transform; discrete wavelet transform; logistic encryption; mean square error; medical image; multiple watermarks; non-interest region; peak signal-to-noise ratio; quantization; region of interest; structural similarity index measure; zigzag sort.