Optimized Video Watermarking With Entropy-Aware Block Selection and Modified Hénon-Map Encryption
Video watermarking is a technique used to embed information into video content, ensuring privacy protection and preventing data misuse. However, watermarking schemes that rely on a single transform method are often vulnerable to noise and geometric distortions. To overcome these limitations, this st...
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| Format: | Article |
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IEEE
2024-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/10788697/ |
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| author | Ranjan K. Senapati Birendra Biswal Sandeep Kautish Gandharba Swain Ayman Altameem Abdulaziz S. Almazyad Ali Wagdy Mohamed |
| author_facet | Ranjan K. Senapati Birendra Biswal Sandeep Kautish Gandharba Swain Ayman Altameem Abdulaziz S. Almazyad Ali Wagdy Mohamed |
| author_sort | Ranjan K. Senapati |
| collection | DOAJ |
| description | Video watermarking is a technique used to embed information into video content, ensuring privacy protection and preventing data misuse. However, watermarking schemes that rely on a single transform method are often vulnerable to noise and geometric distortions. To overcome these limitations, this study introduces a hybrid approach that combines singular value decomposition with discrete wavelet transform and redundant discrete wavelet transform for more effective watermark embedding. The proposed method optimizes the balance between imperceptibility and robustness by fine-tuning the scale factor through a custom fitness function using fruit fly optimization. The watermark is adaptively embedded based on the video’s transform type, sub-band selection, attack types, and keyframes. Block selection within sub-bands is guided by entropy, edge entropy, and contrast. Watermark embedding and extraction are performed on selected blocks that meet these criteria. Experimental results evaluated using metrics such as normalized cross-correlation, image fidelity, and peak signal-to-noise ratio, demonstrate the superiority of our method over state-of-the-art methods. |
| format | Article |
| id | doaj-art-b5bc84ba1cb244c7b70cb7abe56ea6ce |
| institution | OA Journals |
| issn | 2169-3536 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj-art-b5bc84ba1cb244c7b70cb7abe56ea6ce2025-08-20T01:56:57ZengIEEEIEEE Access2169-35362024-01-011219155119157210.1109/ACCESS.2024.351497410788697Optimized Video Watermarking With Entropy-Aware Block Selection and Modified Hénon-Map EncryptionRanjan K. Senapati0https://orcid.org/0000-0003-3375-3378Birendra Biswal1Sandeep Kautish2https://orcid.org/0000-0001-5120-5741Gandharba Swain3https://orcid.org/0000-0001-6586-1432Ayman Altameem4https://orcid.org/0000-0002-9946-423XAbdulaziz S. Almazyad5https://orcid.org/0000-0003-4440-6208Ali Wagdy Mohamed6https://orcid.org/0000-0002-5895-2632Vallurupalli Nageswara Rao Vignana Jyothi Institute of Engineering and Technology, Hyderabad, Telangana, IndiaDepartment of Electronics and Communication Engineering, Center for Medical Imaging Studies, Gayatri Vidya Parishad College of Engineering (Autonomous), Visakhapatnam, Andhra Pradesh, IndiaApex Institute of Technology (AIT-CSE), Chandigarh University, Mohali, Punjab, IndiaDepartment of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Guntur, Andhra Pradesh, IndiaDepartment of Computer Science and Engineering, College of Applied Studies and Community Services, King Saud University, Riyadh, Saudi ArabiaDepartment of Computer Engineering, College of Computer and Information Sciences, King Saud University, Riyadh, Saudi ArabiaOperations Research Department, Faculty of Graduate Studies for Statistical Research, Cairo University, Giza, EgyptVideo watermarking is a technique used to embed information into video content, ensuring privacy protection and preventing data misuse. However, watermarking schemes that rely on a single transform method are often vulnerable to noise and geometric distortions. To overcome these limitations, this study introduces a hybrid approach that combines singular value decomposition with discrete wavelet transform and redundant discrete wavelet transform for more effective watermark embedding. The proposed method optimizes the balance between imperceptibility and robustness by fine-tuning the scale factor through a custom fitness function using fruit fly optimization. The watermark is adaptively embedded based on the video’s transform type, sub-band selection, attack types, and keyframes. Block selection within sub-bands is guided by entropy, edge entropy, and contrast. Watermark embedding and extraction are performed on selected blocks that meet these criteria. Experimental results evaluated using metrics such as normalized cross-correlation, image fidelity, and peak signal-to-noise ratio, demonstrate the superiority of our method over state-of-the-art methods.https://ieeexplore.ieee.org/document/10788697/Copyright protectionconvolutional neural networksdeep learningdiscrete wavelet transformsevolutionary algorithmintellectual property rights |
| spellingShingle | Ranjan K. Senapati Birendra Biswal Sandeep Kautish Gandharba Swain Ayman Altameem Abdulaziz S. Almazyad Ali Wagdy Mohamed Optimized Video Watermarking With Entropy-Aware Block Selection and Modified Hénon-Map Encryption IEEE Access Copyright protection convolutional neural networks deep learning discrete wavelet transforms evolutionary algorithm intellectual property rights |
| title | Optimized Video Watermarking With Entropy-Aware Block Selection and Modified Hénon-Map Encryption |
| title_full | Optimized Video Watermarking With Entropy-Aware Block Selection and Modified Hénon-Map Encryption |
| title_fullStr | Optimized Video Watermarking With Entropy-Aware Block Selection and Modified Hénon-Map Encryption |
| title_full_unstemmed | Optimized Video Watermarking With Entropy-Aware Block Selection and Modified Hénon-Map Encryption |
| title_short | Optimized Video Watermarking With Entropy-Aware Block Selection and Modified Hénon-Map Encryption |
| title_sort | optimized video watermarking with entropy aware block selection and modified h x00e9 non map encryption |
| topic | Copyright protection convolutional neural networks deep learning discrete wavelet transforms evolutionary algorithm intellectual property rights |
| url | https://ieeexplore.ieee.org/document/10788697/ |
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