NSCT domain–based secure multiple‐watermarking technique through lightweight encryption for medical images

Thakur, Sriti; Singh, Amit Kumar; Ghrera, Satya Prakash

doi:10.1002/cpe.5108

Cited by 33 publications

(14 citation statements)

References 30 publications

(61 reference statements)

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“…So the advantage of the Non‐subsampled Contourlet transform is that it not only has translation invariance, multi‐direction, multi‐scale, and anti‐counterfeiting Gibbs distortion, but also can be implemented quickly 28 . The NSCT method is improved from the traditional contourlet change.…”

Section: Methodsmentioning

confidence: 99%

Blind watermarking algorithm combiningNSCT,DWT,SVD, andHVS

Fanfeng

Bai

Xiao

2022

Security and Privacy

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In order to solve the contradiction between watermark transparency and robustness, this paper combines Non-subsampled Contourlet Transformation (NSCT), Discrete Wavelet Transformation (DWT), Singular Value Decomposition (SVD), and Human Visual System (HVS) to improve a watermarking algorithm. Firstly, this algorithm performs a first-level NSCT decomposition on the carrier image to obtain its low-frequency part, and then performs a second-level DWT on the low-frequency part, extracts its second-level low-frequency sub bands and block these sub bands to sub-blocks according to their size. Secondly, SVD is performed for each sub-block and the best embedding position of the watermark according to the sensitivity of HVS for the average brightness and the modified cosine similarity measurement method is calculated. Finally, the watermark scrambled and encrypted by Arnold is embedded into the selected singular value. This algorithm can realize the blind extraction of watermark. Experimental results show that the algorithm can not only satisfy the transparency but the robustness of the watermark at the same time as well. K E Y W O R D Sblind watermarking, digital watermarking, discrete wavelet transform, NSCT, singular value decomposition INTRODUCTIONNowadays, multimedia documents like images, audio, and video are easy to store and disseminate with the help of digital communication through internet. The document, however, can be modified by intruders during transmission or storage for illegal use. This illegal alteration is becoming a problem in many human-centric applications. Therefore, the effective protection and content certification of digital products have become a real problem and one can incorporate digital watermarking scheme to deal with such issues. Digital watermarking technology uses the principle of information hiding to embed the logo information into the carrier data in a perceptible or imperceptible way, without affecting the use value of the original carrier, protecting copyright, private communication, content authentication, and tracking infringements. 1 Digital watermarking can be applied to images, videos, audio, or texts. 2 The embedded information should be protected and extracted successfully to verify the image. Digital image watermarking can be of two types: visible and invisible. For invisible watermarking, there should not be any perceptual change in the host image. In visible watermarking, the watermark should can be seen so that the watermark can be easily detected. 3 Watermarking can be classified into blind and non-blind watermarking depending

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Section: Methodsmentioning

confidence: 99%

Blind watermarking algorithm combiningNSCT,DWT,SVD, andHVS

Fanfeng

Bai

Xiao

2022

Security and Privacy

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“…Color image watermarking is quite like the grayscale watermarking, but only the difference is, there are three color components like red, green, and blue. Recently, the interest in security of copyrights have been enhanced in several fields like military, bioinformatics, medical, 16 biometric, 13 and webserver applications, 17 and so on.…”

Section: Introductionmentioning

confidence: 99%

A new video watermarking using redundant discrete wavelet in singular value decomposition domain with multi‐objective optimization

Kumar¹,

Srinivas²,

Prabhakar

2021

Concurrency and Computation

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Day by day, the transmission or sharing of digital information online is increasing due to the fact that Internet usage has become somewhat of an addiction for the majority of people. This results in larger copyright violation problems. Nowadays, most of the data or information is being transmitted in the form of digital images or videos, which are rather simple for the violators of copyright to forge or fake and then share for profit. Thus, digital watermarking came into existence as a possible solution to address these violations of copyright. This article proposes a new blind video watermarking (BVW) using redundant discrete wavelet transform (RDWT) in singular value decomposition (SVD) domain, which utilizes the advantages of both RDWT and SVD to embed and extract the watermark information into the cover video without degrading the quality of the watermark. In addition, an efficient meta‐heuristic optimization with multi‐objective optimization (MOO) is employed to further optimize the proposed RDWT‐SVD approach. Further, various attacks were applied to the watermarked frame to disclose the robustness of proposed BVW using RDWT‐SVD with MOO approach. Extensive simulations on several test videos with comparison to the conventional BVW methodologies exhibit the transcendency of the proposed BVW using RDWT‐SVD with MOO approach in terms of watermarking quality evaluation metrics such as peak signal‐to‐noise ratio (PSNR), structural similarity index, normalized correlation, and even that of root mean square error as well.

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“…In the meantime, the embedding process can also be completed in the transformed domains, e.g. the discrete cosine transform (DCT) [6]- [11], discrete Fourier transform (DFT) [12]- [14], discrete wave transformation (DWT) [15]- [17], and singular value decomposition (SVD) [10], [11], [18]- [21]. To ensure the robustness of the embedding algorithms, frequency domain analysis is utilized to find out the possible locations of the embedding watermark coefficients [16], [22].…”

Section: Introductionmentioning

confidence: 99%

An Optimized Image Watermarking Method Based on HD and SVD in DWT Domain

et al. 2019

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In this paper, a novel image watermarking method is proposed which is based on discrete wave transformation (DWT), Hessenberg decomposition (HD), and singular value decomposition (SVD). First, in the embedding process, the host image is decomposed into a number of sub-bands through multilevel DWT, and the resulting coefficients of which are then used as the input for HD. The watermark is operated on the SVD at the same time. The watermark is finally embedded into the host image by the scaling factor. Fruit fly optimization algorithm, one of the natural-inspired optimization algorithms is devoted to find the scaling factor through the proposed objective evaluation function. The proposed method is compared to other research works under various spoof attacks, such as the filter, noise, JPEG compression, JPEG2000 compression, and sharpening attacks. The experimental results show that the proposed image watermarking method has a good trade-off between robustness and invisibility even for the watermarks with multiple sizes.INDEX TERMS Image watermarking, discrete wave transformation, singular value decomposition, Hessenberg decomposition, fruit fly optimization algorithm.

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NSCT domain–based secure multiple‐watermarking technique through lightweight encryption for medical images

Cited by 33 publications

References 30 publications

Blind watermarking algorithm combiningNSCT,DWT,SVD, andHVS

Blind watermarking algorithm combiningNSCT,DWT,SVD, andHVS

A new video watermarking using redundant discrete wavelet in singular value decomposition domain with multi‐objective optimization

An Optimized Image Watermarking Method Based on HD and SVD in DWT Domain

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