Zero-Watermarking Algorithm for Medical Images Based on Dual-Tree Complex Wavelet Transform and Discrete Cosine Transform

Liu, Jing; Li, Jingbing; Zhang, Kun; Bhatti, Uzair Aslam; Ai, Yang

doi:10.1166/jmihi.2019.2559

Cited by 42 publications

(14 citation statements)

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“…We compared the proposed algorithm with two other zero-watermark algorithms, which are based on DCT and DTCWT-DCT [27], respectively. e comparison results are shown in Table 5.…”

Section: Comparison With Other Algorithmsmentioning

confidence: 99%

Robust and Secure Zero-Watermarking Algorithm for Medical Images Based on Harris-SURF-DCT and Chaotic Map

Gong

Bhatti

et al. 2021

Security and Communication Networks

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To protect the patient information in medical images, this article proposes a robust watermarking algorithm for medical images based on Harris-SURF-DCT. First, the corners of the medical image are extracted using the Harris corner detection algorithm, and then, the previously extracted corners are described using the method of describing feature points in the SURF algorithm to generate the feature descriptor matrix. Then, the feature descriptor matrix is processed through the perceptual hash algorithm to obtain the feature vector of the medical image, which is a binary feature vector with a size of 32 bits. Secondly, to enhance the security of the watermark information, the logistic map algorithm is used to encrypt the watermark before embedding the watermark. Finally, with the help of cryptography knowledge, third party, and zero-watermarking technology, the algorithm can embed the watermark without modifying the medical image. When extracting the watermark, the algorithm can extract the watermark from the test image without the original image. In addition, the algorithm has strong robustness to conventional attacks and geometric attacks. Especially under geometric attacks, the algorithm performs better.

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“…We compared the proposed algorithm with two other zero-watermark algorithms, which are based on DCT and DTCWT-DCT [27], respectively. e comparison results are shown in Table 5.…”

Section: Comparison With Other Algorithmsmentioning

confidence: 99%

Robust and Secure Zero-Watermarking Algorithm for Medical Images Based on Harris-SURF-DCT and Chaotic Map

Gong

Bhatti

et al. 2021

Security and Communication Networks

Self Cite

View full text Add to dashboard Cite

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“…In both of those applications the association between a coefficients and its parent is used. Though sub-sampling is reasonable for denoising applications, the DTCWT's subsampled sub-bands have a limited number of coefficients directly linked to each spatial location in the image or signal, a relationship that often contradicts the needs of applications for analysis [15], [16]. To can such analysis we define a lifting form of the DTCWT.…”

Section: Lifting Dual Tree Complex Wavelet Transformmentioning

confidence: 99%

Lifting dual tree complex wavelets transform

Naimi

Adamou-Mitiche

Mitiche

2021

IJECE

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We describe the lifting dual tree complex wavelet transform (LDTCWT), a type of lifting wavelets remodeling that produce complex coefficients by employing a dual tree of lifting wavelets filters to get its real part and imaginary part. Permits the remodel to produce approximate shift invariance, directionally selective filters and reduces the computation time (properties lacking within the classical wavelets transform). We describe a way to estimate the accuracy of this approximation and style appropriate filters to attain this. These benefits are often exploited among applications like denoising, segmentation, image fusion and compression. The results of applications shrinkage denoising demonstrate objective and subjective enhancements over the dual tree complex wavelet transform (DTCWT). The results of the shrinkage denoising example application indicate empirical and subjective enhancements over the DTCWT. The new transform with the DTCWT provide a trade-off between denoising computational competence of performance, and memory necessities. We tend to use the PSNR (peak signal to noise ratio) alongside the structural similarity index measure (SSIM) and the SSIM map to estimate denoised image quality.

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“…Shaman's assistants explained the contents of the sacrifices to the participants and reported the purpose of the sacrifices to the gods. People began offering sacrifices to the gods, and then the gods would descend on the shaman [11]. Then the assistant will sing to the Shaman on behalf of the Oroqen people to pray for the gods to protect the people's wealth and health.…”

Section: ) the Analysis Of The Structure Of The Spring Festival Dancementioning

confidence: 99%

Study on the Structure and Form of the Shaman Dance in the Fishing and Hunting Nationalities

Ma¹

2019

Proceedings of the 2nd International Seminar on Education Research and Social Science (ISERSS 2019)

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The article sorts out and summarises the results of Shaman dance research. Analyse the structural fo rm o f Shaman dance in the shamanic religious rituals by taking the semiotics research method and analysing the social function of Shaman dance and its realisation through the use of the "structuralfunctional" theory in cultural chemistry. This provides a basis for studying some fundamental issues between Shaman dance and the survival of minorities.

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Zero-Watermarking Algorithm for Medical Images Based on Dual-Tree Complex Wavelet Transform and Discrete Cosine Transform

Cited by 42 publications

References 0 publications

Robust and Secure Zero-Watermarking Algorithm for Medical Images Based on Harris-SURF-DCT and Chaotic Map

Robust and Secure Zero-Watermarking Algorithm for Medical Images Based on Harris-SURF-DCT and Chaotic Map

Lifting dual tree complex wavelets transform

Study on the Structure and Form of the Shaman Dance in the Fishing and Hunting Nationalities

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