Robust block-based watermarking algorithm with parallelization using multi-level discrete wavelet transformation

In today’s digital era, the need to safeguard the authenticity and ownership of media content shared online via social networking sites and apps has become increasingly crucial. Digital watermarking emerges as a viable solution to address this need by providing authentication and ownership verificat...

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Vydáno v:Journal of real-time image processing Ročník 21; číslo 6; s. 182
Hlavní autoři: Yadav, Akash, Goyal, Jitendra, Ahmed, Mushtaq
Médium: Journal Article
Jazyk:angličtina
Vydáno: Berlin/Heidelberg Springer Berlin Heidelberg 01.12.2024
Springer Nature B.V
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ISSN:1861-8200, 1861-8219
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Shrnutí:In today’s digital era, the need to safeguard the authenticity and ownership of media content shared online via social networking sites and apps has become increasingly crucial. Digital watermarking emerges as a viable solution to address this need by providing authentication and ownership verification of digital media. Various watermarking techniques have been proposed in spatial and transformation domains, with ongoing efforts to enhance robustness against common watermarking attacks, such as filtering, noise, and transformations. In this paper, we introduce a novel block-based parallelized watermarking method. Our proposed approach hides binary watermarks within grayscale images by employing multi-level discrete wavelet transformation on image blocks in parallel. A pixel scramble mechanism is also employed to strengthen security measures. The effectiveness of the proposed method is evaluated using three quality metrics: structural similarity index measure and peak signal-to-noise ratio to assess the imperceptibility of watermarked images and normalized correlation to evaluate the robustness of our approach against standard watermarking attacks. Experimental results show that our method achieves high PSNR values of up to 48.63 dB and SSIM values above 0.99, indicating excellent imperceptibility. Additionally, NC values close to 1.0 across various attack scenarios demonstrate superior robustness compared to existing methods.
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ISSN:1861-8200
1861-8219
DOI:10.1007/s11554-024-01559-w