Robust Complementary Dual Image Watermarking in Subbands Derived from the Laplacian Pyramid, Discrete Wavelet Transform, and Directional Filter Bank

Hu, Hwai-Tsu; Lee, Tung-Tsun

doi:10.1007/s00034-022-01975-y

Cited by 5 publications

(2 citation statements)

References 35 publications

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“…Since local image feature descriptors are invariant and distinguishable, existing watermarking algorithms are often combined with feature descriptors [24]. Commonly used feature descriptors are SIFT (Scale Invariant Feature Transform) [20,25,26], SURF (Speeded Up Robust Features) [22][23][24], FAST (Features from accelerated segment test) [26], Daisy [27] etc. Fang et al [20] used the SIFT algorithm to extract image features and perform bandelet transform and DCT on their characteristics to obtain the feature vector of medical images.…”

Section: Introductionmentioning

confidence: 99%

“…Transform domain watermarking is performed by adjusting the coefficients of the image transform domain for watermark embedding [13,14], and this type of algorithm has the characteristics of more complex operations, less information capacity, but high resistance to attacks. The commonly used transform domains are DCT [4,6,15,[18][19][20][21], DWT [1,3,5,10,[15][16][17]22], DFT (Discrete Fourier Transform) [18], SVD (Singular Value Decomposition) [16,17,21] etc. Using a single transform domain does not meet the needs of all watermarking algorithms simultaneously, and to compensate for each other's shortcomings, most existing algorithms use hybrid domain techniques.…”

Section: Introductionmentioning

confidence: 99%

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Robust zero‐watermarking algorithm based on discrete wavelet transform and daisy descriptors for encrypted medical image

Yuan,

Li,

Liu

et al. 2024

CAAI Trans on Intel Tech

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In the intricate network environment, the secure transmission of medical images faces challenges such as information leakage and malicious tampering, significantly impacting the accuracy of disease diagnoses by medical professionals. To address this problem, the authors propose a robust feature watermarking algorithm for encrypted medical images based on multi‐stage discrete wavelet transform (DWT), Daisy descriptor, and discrete cosine transform (DCT). The algorithm initially encrypts the original medical image through DWT‐DCT and Logistic mapping. Subsequently, a 3‐stage DWT transformation is applied to the encrypted medical image, with the centre point of the LL3 sub‐band within its low‐frequency component serving as the sampling point. The Daisy descriptor matrix for this point is then computed. Finally, a DCT transformation is performed on the Daisy descriptor matrix, and the low‐frequency portion is processed using the perceptual hashing algorithm to generate a 32‐bit binary feature vector for the medical image. This scheme utilises cryptographic knowledge and zero‐watermarking technique to embed watermarks without modifying medical images and can extract the watermark from test images without the original image, which meets the basic requirements of medical image watermarking. The embedding and extraction of watermarks are accomplished in a mere 0.160 and 0.411s, respectively, with minimal computational overhead. Simulation results demonstrate the robustness of the algorithm against both conventional attacks and geometric attacks, with a notable performance in resisting rotation attacks.

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