Robust JND-Guided Video Watermarking via Adaptive Block Selection and Temporal Redundancy
This paper introduces a robust and imperceptible video watermarking framework designed for blind extraction in dynamic video environments. The proposed method operates in the spatial domain and combines multiscale perceptual analysis, adaptive Just Noticeable Difference (JND)-based quantization, and...
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MDPI AG
2025-08-01
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| Series: | Mathematics |
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| author | Antonio Cedillo-Hernandez Lydia Velazquez-Garcia Manuel Cedillo-Hernandez Ismael Dominguez-Jimenez David Conchouso-Gonzalez |
| author_facet | Antonio Cedillo-Hernandez Lydia Velazquez-Garcia Manuel Cedillo-Hernandez Ismael Dominguez-Jimenez David Conchouso-Gonzalez |
| author_sort | Antonio Cedillo-Hernandez |
| collection | DOAJ |
| description | This paper introduces a robust and imperceptible video watermarking framework designed for blind extraction in dynamic video environments. The proposed method operates in the spatial domain and combines multiscale perceptual analysis, adaptive Just Noticeable Difference (JND)-based quantization, and temporal redundancy via multiframe embedding. Watermark bits are embedded selectively in blocks with high perceptual masking using a QIM strategy, and the corresponding DCT coefficients are estimated directly from the spatial domain to reduce complexity. To enhance resilience, each bit is redundantly inserted across multiple keyframes selected based on scene transitions. Extensive simulations over 21 benchmark videos (CIF, 4CIF, HD) validate that the method achieves superior performance in robustness and perceptual quality, with an average Bit Error Rate (BER) of 1.03%, PSNR of 50.1 dB, SSIM of 0.996, and VMAF of 97.3 under compression, noise, cropping, and temporal desynchronization. The system outperforms several recent state-of-the-art techniques in both quality and speed, requiring no access to the original video during extraction. These results confirm the method’s viability for practical applications such as copyright protection and secure video streaming. |
| format | Article |
| id | doaj-art-4aa86a56048e4dc4948bdf4f90d9db0f |
| institution | Kabale University |
| issn | 2227-7390 |
| language | English |
| publishDate | 2025-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Mathematics |
| spelling | doaj-art-4aa86a56048e4dc4948bdf4f90d9db0f2025-08-20T03:36:26ZengMDPI AGMathematics2227-73902025-08-011315249310.3390/math13152493Robust JND-Guided Video Watermarking via Adaptive Block Selection and Temporal RedundancyAntonio Cedillo-Hernandez0Lydia Velazquez-Garcia1Manuel Cedillo-Hernandez2Ismael Dominguez-Jimenez3David Conchouso-Gonzalez4Tecnologico de Monterrey, Escuela de Ingenieria y Ciencias, Av. Eugenio Garza Sada 2501 Sur, Col. Tecnologico, Monterrey 64700, Nuevo León, MexicoInstituto Politecnico Nacional, Centro de Investigaciones Economicas, Administrativas y Sociales, Lauro Aguirre 120, Agricultura, Ciudad de MeXico 11360, MexicoInstituto Politecnico Nacional, Escuela Superior de Ingenieria Mecanica y Electrica, Unidad Culhuacan, Av. Santa Ana 1000, San Francisco Culhuacan, Coyoacan, Ciudad de Mexico 04440, MexicoUniversidad Autonoma del Estado de Hidalgo, Escuela Superior de Tlahuelilpan, Sergio Butron Casas 19, La Rancheria, Col. Centro, Tlahuelilpan 42780, Hidalgo, MexicoTecnologico de Monterrey, Escuela de Ingenieria y Ciencias, Av. Eugenio Garza Sada 2501 Sur, Col. Tecnologico, Monterrey 64700, Nuevo León, MexicoThis paper introduces a robust and imperceptible video watermarking framework designed for blind extraction in dynamic video environments. The proposed method operates in the spatial domain and combines multiscale perceptual analysis, adaptive Just Noticeable Difference (JND)-based quantization, and temporal redundancy via multiframe embedding. Watermark bits are embedded selectively in blocks with high perceptual masking using a QIM strategy, and the corresponding DCT coefficients are estimated directly from the spatial domain to reduce complexity. To enhance resilience, each bit is redundantly inserted across multiple keyframes selected based on scene transitions. Extensive simulations over 21 benchmark videos (CIF, 4CIF, HD) validate that the method achieves superior performance in robustness and perceptual quality, with an average Bit Error Rate (BER) of 1.03%, PSNR of 50.1 dB, SSIM of 0.996, and VMAF of 97.3 under compression, noise, cropping, and temporal desynchronization. The system outperforms several recent state-of-the-art techniques in both quality and speed, requiring no access to the original video during extraction. These results confirm the method’s viability for practical applications such as copyright protection and secure video streaming.https://www.mdpi.com/2227-7390/13/15/2493video watermarkingperceptual modeltemporal redundancyQIMJNDblind extraction |
| spellingShingle | Antonio Cedillo-Hernandez Lydia Velazquez-Garcia Manuel Cedillo-Hernandez Ismael Dominguez-Jimenez David Conchouso-Gonzalez Robust JND-Guided Video Watermarking via Adaptive Block Selection and Temporal Redundancy Mathematics video watermarking perceptual model temporal redundancy QIM JND blind extraction |
| title | Robust JND-Guided Video Watermarking via Adaptive Block Selection and Temporal Redundancy |
| title_full | Robust JND-Guided Video Watermarking via Adaptive Block Selection and Temporal Redundancy |
| title_fullStr | Robust JND-Guided Video Watermarking via Adaptive Block Selection and Temporal Redundancy |
| title_full_unstemmed | Robust JND-Guided Video Watermarking via Adaptive Block Selection and Temporal Redundancy |
| title_short | Robust JND-Guided Video Watermarking via Adaptive Block Selection and Temporal Redundancy |
| title_sort | robust jnd guided video watermarking via adaptive block selection and temporal redundancy |
| topic | video watermarking perceptual model temporal redundancy QIM JND blind extraction |
| url | https://www.mdpi.com/2227-7390/13/15/2493 |
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