Watermarking Algorithm Based on Kernel Fuzzy Clustering and Singular Value Decomposition in the Complex Wavelet Transform Domain

Purpose The purpose of this paper is to present an improved wavelet based approach in single image super resolution (SISR). The proposed method generates high resolution (HR) images by preserving the image contrast and edges simultaneously. Design/methodology/approach Covariance based interpolation algorithm is employed to obtain an initial estimate of the unknown HR image. The proposed method preserves the image contrast, by applying singular value decomposition (SVD) based correction on the dual-tree complex wavelet transform (DT-CWT) coefficients. In addition, the dual operating mode diffusion based shock filter (DBSF) ensures noise mitigation and edge preservation. Findings Experimental results on various test images reveal superiority of the proposed method over the existing SISR techniques in terms of peak signal to noise ratio (PSNR), structural similarity index measure (SSIM) and visual quality. Originality/value With SVD based correction, the proposed method preserves the image contrast and also the DBSF operation helps to achieve sharper edges.

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Integrated Discrete Wavelet Transform and Singular Value Decomposition based Biometric Watermarking for Authentication using Iris Images

International Journal of Recent Technology and Engineering - 2 ◽

10.35940/ijrte.d8502.118419 ◽

2019 ◽

Vol 8 (4) ◽

pp. 4672-4679

Keyword(s):

Wavelet Transform ◽

Singular Value Decomposition ◽

Digital Watermarking ◽

Singular Value ◽

The Other ◽

Discrete Wavelet ◽

Transform Domain ◽

Biometric Recognition ◽

Value Decomposition ◽

Biometric Information

Recently with respect to developments in watermarking techniques, intruders are capable of accessing the database. Several strategies are designed for securing information. Utilization of watermarks will be recommended with the background pertaining to several biometric strategies comprising fingerprints, position of palm, gait, iris, speech, etc. Among the available approaches digital watermarking will be one of the effective techniques. Prominent manner of carrying out the digital watermarking will be spatial domain along with strong transform domain. This paper establishes a strategy for providing the watermark, besides biometric information by utilizing Wavelet Transform in addition to Singular Value Decomposition. Utilization of biometric rather than conservative watermark enhances protection of information. The utilized biometric will be iris. Consideration of iris template as watermark guarantees iris pattern communication, whereas watermarking iris images might be involved in assisting, safeguarding of information in addition to identification of iris image moderation. The mentioned work involved in carrying out analysis means checking the authentication under various attacks along with no attacks. Motivation in utilization of watermarking will depend on enhancement in the field of biometric recognition. On the other hand, utilization of biometric patterns as “message” has to be designed with conservative strong watermarking for safeguarding the information. So as to ensure biometric appreciation to the development of watermark.

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Mixed Noise Removal for Images Using the FINDRM with the Directional Difference and the BSF in the Dual-Tree Complex Wavelet Transform Domain

IEEJ Transactions on Electronics Information and Systems ◽

10.1541/ieejeiss.130.863 ◽

2010 ◽

Vol 130 (5) ◽

pp. 863-872

Author(s):

Song Li ◽

Shingo Kuroiwa ◽

Hiroo Sekiya ◽

Yeqiu Li ◽

Caizhu Wang ◽

...

Keyword(s):

Wavelet Transform ◽

Noise Removal ◽

Transform Domain ◽

Complex Wavelet Transform ◽

Mixed Noise ◽

Complex Wavelet ◽

Mixed Noise Removal ◽

Directional Difference

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LWT-DCT based Image Watermarking Scheme using Normalized SVD

Recent Advances in Computer Science and Communications ◽

10.2174/2666255813999200821161656 ◽

2020 ◽

Vol 13 ◽

Author(s):

Rahul Dixit ◽

Amita Nandal ◽

Arvind Dhaka ◽

Vardan Agarwal ◽

Yohan Varghese

Keyword(s):

Wavelet Transform ◽

Singular Value Decomposition ◽

Discrete Cosine Transform ◽

Image Watermarking ◽

Singular Value ◽

Cover Image ◽

Lifting Wavelet Transform ◽

Cosine Transform ◽

Lifting Wavelet ◽

Value Decomposition

Background: Nowadays information security is one of the biggest issues of social networks. The multimedia data can be tampered with, and the attackers can then claim its ownership. Image watermarking is a technique that is used for copyright protection and authentication of multimedia. Objective: We aim to create a new and more robust image watermarking technique to prevent illegal copying, editing and distribution of media. Method : The watermarking technique proposed in this paper is non-blind and employs Lifting Wavelet Transform on the cover image to decompose the image into four coefficient matrices. Then Discrete Cosine Transform is applied which separates a selected coefficient matrix into different frequencies and later Singular Value Decomposition is applied. Singular Value Decomposition is also applied to the watermarking image and it is added to the singular matrix of the cover image which is then normalized followed by the inverse Singular Value Decomposition, inverse Discrete Cosine Transform and inverse Lifting Wavelet Transform respectively to obtain an embedded image. Normalization is proposed as an alternative to the traditional scaling factor. Results: Our technique is tested against attacks like rotation, resizing, cropping, noise addition and filtering. The performance comparison is evaluated based on Peak Signal to Noise Ratio, Structural Similarity Index Measure, and Normalized Cross-Correlation. Conclusion: The experimental results prove that the proposed method performs better than other state-of-the-art techniques and can be used to protect multimedia ownership.

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