A Robust Watermarking Algorithm for Medical Images Based on DWT-Daisy and Discrete Cosine Transform

Yuan, Yazhou; Li, Jingbing; Liu, Jing; Bhatti, Uzair Aslam; Chen, Yen Wei

doi:10.1007/978-981-99-3311-2_18

Cited by 3 publications

(1 citation statement)

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“…Yuan et al [18] present a robust medical watermarking algorithm designed to protect patients' privacy during medical data transmission. Their approach employs multilevel discrete wavelet transform (M-DWT), Daisy descriptor, and discrete cosine transform (DCT).…”

Section: Literature Reviewmentioning

confidence: 99%

In-depth exploration of digital image watermarking with discrete cosine transform and discrete wavelet transform

Apu Hosen,

Hoshen Moz,

Shalauddin Kabir

et al. 2024

IJEECS

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Digital image watermarking is a crucial technique used to protect the integrity and ownership of digital images by embedding imperceptible watermarks into the image content. This review concentrates on the utilization of discrete cosine transform (DCT) and discrete wavelet transform (DWT) in digital image watermarking schemes. DCT, widely used in image compression like JPEG, is an attractive choice for watermarking, modifying DCT coefficients with minimal impact on image quality. On the other hand, DWT offers multiresolution representation, enabling better localization and robustness against attacks. DWT-based methods use wavelet coefficients to embed watermarks in specific frequency bands or image regions. The review examines the strengths and weaknesses of DCT and DWT in digital image watermarking, exploring algorithms and approaches proposed in the literature. It also addresses challenges like attacks, synchronization, and robustness to image processing. Additionally, a comparative analysis of DCT and DWT-based methods considers imperceptibility, robustness, capacity, and computational complexity. By offering valuable insights, this review aids researchers and practitioners in implementing secure and efficient digital image watermarking solutions.

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Section: Literature Reviewmentioning

confidence: 99%