Comparative Analysis of Digital Image Watermarking Based on Lifting Wavelet Transform and Singular Value Decomposition

Naaz, Sameena; Sana, Ehtesham; Ansari, Iffat Rehman

doi:10.1007/978-981-15-0339-9_7

Cited by 1 publication

(1 citation statement)

References 11 publications

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“…Note that although various traditional image data hiding approaches have been reported, the interesting contributions of the proposed methods include the following four aspects: • We propose an image data hiding scheme based on LWT-HD-RSVD, which can provide both invisibility and robustness. LWT provides various advantages such as less distortion, low aliasing effect, very less memory requirement, low computation cost and reconstruction is very good [12]. The more precise components of the host image are obtained by HD [13].…”

Section: Introductionmentioning

confidence: 99%

Data hiding in encryption–compression domain

Singh

2021

Complex Intell. Syst.

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This paper introduces a robust and secure data hiding scheme to transmit grayscale image in encryption-then-compression domain. First, host image is transformed using lifting wavelet transform, Hessenberg decomposition and redundant singular value decomposition. Then, we use appropriate scaling factor to invisibly embed the singular value of watermark data into the lower frequency sub-band of the host image. We also use suitable encryption-then-compression scheme to improve the security of the image. Additionally, de-noising convolutional neural network is performed at extracted mark data to enhance the robustness of the scheme. Experimental results verify the effectiveness of our scheme, including embedding capacity, robustness, invisibility, and security. Further, it is established that our scheme has a better ability to recover concealed mark than conventional ones at low cost.

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Section: Introductionmentioning

confidence: 99%

Data hiding in encryption–compression domain

Singh

2021

Complex Intell. Syst.

View full text Add to dashboard Cite

show abstract

Comparative Analysis of Digital Image Watermarking Based on Lifting Wavelet Transform and Singular Value Decomposition

Cited by 1 publication

References 11 publications

Data hiding in encryption–compression domain

Data hiding in encryption–compression domain

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