Academic Journal

Authentication of Lung CT-Scan Data in NIfTI Format Using LWT, Hessenberg Decomposition, and Affine Transform.

Bibliographic Details
Title: Authentication of Lung CT-Scan Data in NIfTI Format Using LWT, Hessenberg Decomposition, and Affine Transform.
Authors: Singh, Kamred Udham, Kumar, Ankit, Singh, Teekam
Source: IETE Journal of Research; Apr2024, Vol. 70 Issue 4, p3590-3602, 13p
Subject Terms: Digital image watermarking, Technological innovations, Matrix decomposition, Digital watermarking, Image processing, Technological progress
Abstract: Technological advancement in digital medical imaging changes the world health care system because various diseases are diagnosed through these technologies. In the Covid-19 phase, telemedicine played a tremendous role in providing remote medical consultation in rural areas. But in remote consultation, various medical images send to a radiologist for diagnosis through the internet. Worldwide has seen a significant surge in digital media attacks that replicate and tamper with the digital image, resulting in a breach of authenticity and ownership. A robust and safe watermarking scheme for NIfTI images has been proposed in this paper. This novel method entails meticulously integrating a watermark in the slice of the NIfTI image. We aim to correctly incorporate the watermark with minimal distortion and retain the medical information of the selected image slice. The proposed method uses LWT transform to transform the image, allowing for surprisingly good modification during insertion. Furthermore, Hessenberg matrix decomposition is applied on the LL sab bands with the image's maximal energy to be retained. Scrambling the watermark before embedding it in the slice is accomplished using the Affine transform. A thorough study of the trade-off between security, imperceptibility, and robustness utilizing performance measures viz. NC, PSNR, SNR, and SSIM have been given. The simulation findings have been validated against image processing threats. [ABSTRACT FROM AUTHOR]
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Database: Complementary Index
Description
ISSN:03772063
DOI:10.1080/03772063.2023.2195372