EDP Sciences logo
Web of Conferences logo
Search
Menu
All issues Volume 360 (2026) EPJ Web Conf., 360 (2026) 01024 References
Open Access
Issue
EPJ Web Conf.
Volume 360, 2026
1st International Conference on “Quantum Innovations for Computing and Knowledge Systems” (QUICK’26)
Article Number 01024
Number of page(s) 16
DOI https://doi.org/10.1051/epjconf/202636001024
Published online 23 March 2026
  1. S. Dhar and A.K. Sahu, “Digital to quantum watermarking: A journey from past to present and into the future,” Computer Science Review, vol. 54, p. 100679, (2024). [Online]. Available: https://www.sciencedirect.com/science/article/pii/S1574013724000637 [Google Scholar]
  2. R. A. Khan, “A flexible representation of quantum images for polynomial preparation, image compression, and processing operations,” Quantum Information Processing, vol. 18, no. 7, p. 201, (2019). [Online]. Available: https://doi.org/10.1007/s11128-019-2306-6 [Google Scholar]
  3. S. Iranmanesh, R. Atta, and M. Ghanbari, “Implementation of a quantum image watermarking scheme using neqr on ibm quantum experience,” Quantum Information Processing, vol. 21, no. 6, p. 194, (2022). [Online]. Available: https://doi.org/10.1007/s11128-022-03530-9 [Google Scholar]
  4. M. Refiyanti, G. Budiman, and L. Novamizanti, “Quantum image water-marking based on quantum state modification using rotation gate,” in 2024 International Conference on Artificial Intelligence, Blockchain, Cloud Computing, and Data Analytics (ICoABCD), (2024), pp. 178–183. [Online]. Available: https://ieeexplore.ieee.org/document/10704405 [Google Scholar]
  5. N.-R. Zhou, J.-W. Wu, M.-X. Chen, and M.-M. Wang, “A quantum image encryption and watermarking algorithm based on qdct and baker map,” International Journal of Theoretical Physics, vol. 63, no. 4, p. 100, (2024). Available: https://doi.org/10.1007/s10773-024-05630-x [Google Scholar]
  6. Y. Yu, J. Gao, X. Mu, and S. Wang, “Adaptive lsb quantum image watermarking algorithm based on haar wavelet transforms,” Quantum Information Processing, vol. 22, no. 5, p. 180, (2023). Available: https://doi.org/10.1007/s11128-023-03926-1 [Google Scholar]
  7. R. K. Singh, K. N. Tripathi, G. Kaur, and R. Agrawal, “Qmcs-ias: Quantum mechanism and compression sensing-based image authentication and security technique,” Multimedia Tools and Applications, vol. 84, no. 27, pp. 32 209–32 235, (2025). [Online]. Available: https://doi.org/10.1007/s11042-024-20474- [Google Scholar]
  8. Zhu, X. Chen, and Y. Yang, “A blind watermarking scheme for tmqir images,” Multimedia Tools and Applications, vol. 83, no. 8, pp. 23 109–23 127, (2024). [Online]. Available: https://doi.org/10.1007/s11042-023-15368-z [Google Scholar]
  9. M.-X. Wang, H.-M. Yang, D.-H. Jiang, B. Yan, J.-S. Pan, and T. Wang, “A novel quantum image watermarking scheme for tamper localization and self-recovery,” Quantum Information Processing, vol. 21, no. 8, p. 277, (2022). [Online]. Available: https://doi.org/10.1007/s11128-022-03619-1 [Google Scholar]
  10. Z. Xing, C.-T. Lam, X. Yuan, G. Huang, and P. Machado, “A novel geometrically invariant quantum watermarking scheme utilizing quantum error correction,” Journal of King Saud University - Computer and Information Sciences, vol. 35, no. 10, p. 101818, (2023). [Online]. Available: https://www.sciencedirect.com/science/article/pii/S1319157823003725 [Google Scholar]
  11. X. Mu, H. Wang, R. Bao, S. Wang, and H. Ma, “An improved quantum watermarking using quantum haar wavelet transform and qsobel edge detection,” Quantum Information Processing, vol. 22, no. 5, p. 223, (2023). [Online]. Available: https://doi.org/10.1007/s11128-023-03964-9 [Google Scholar]
  12. Z. Xing, X. Yuan, and C.-T. Lam, “A quantum watermarking scheme using new enhanced quantum image representation,” in 2023 8th International Conference on Signal and Image Processing (ICSIP), (2023), pp. 326–330. [Online]. Available: https://ieeexplore.ieee.org/document/10270930 [Google Scholar]
  13. R. Gorle and A. Guttavelli, “A novel dynamic image watermarking technique with features inspired by quantum computing principles,” AIP Advances, vol. 14, no. 4, p. 045024, (2024). [Online]. Available: https://doi.org/10.1063/5.0209417 [Google Scholar]
  14. J. Su, X. Guo, C. Liu, and L. Li, “A new trend of quantum image representations,” IEEE Access, vol. 8, pp. 214 520–214 537, (2020). [Online]. Available: https://ieeexplore.ieee.org/document/9268129 [Google Scholar]
  15. P. Easom-McCaldin, A. Bouridane, A. Belatreche, R. Jiang, and S. Al-Maadeed, “Efficient quantum image classification using single qubit encoding,” IEEE Transactions on Neural Networks and Learning Systems, vol. 35, no. 2, pp. 1472–1486, (2024). [Online]. Available: https://ieeexplore.ieee.org/document/9798852 [Google Scholar]
  16. Z. Xing, C.-T. Lam, X. Yuan, S.-K. Im, and P. Machado, “Mmqw: Multi-modal quantum watermarking scheme,” IEEE Transactions on Information Forensics and Security, vol. 19, pp. 5181–5195, (2024). [Online]. Available: https://ieeexplore.ieee.org/document/10509727 [Google Scholar]
  17. Z. Xing, X. Yuan, C.-T. Lam, and P. Machado, “Ngqr: A novel generalized quantum image representation,” IEEE Transactions on Emerging Topics in Computing, vol. 13, no. 3, pp. 591–603, (2025). [Online]. Available: https://ieeexplore.ieee.org/document/10706768 [Google Scholar]
  18. Z. Xing, X. Yuan, and C.-T. Lam, “Pattern-based quantum text watermarking: Securing digital content with next-gen quantum techniques,” iScience, vol. 27, no. 12, p. 111364, (2024). [Online]. Available: https://www.sciencedirect.com/science/article/pii/S2589004224025896 [Google Scholar]
  19. “Dwt-dct image watermarking with quantum-inspired optimization,” International Journal of Intelligent Engineering and Systems, (2025). [Online]. Available: https://api.semanticscholar.org/CorpusID:275059671 [Google Scholar]
  20. J.-W. Jiang, T. Zhang, W. Li, and S.-M. Wang, “A quantum image watermarking scheme based on quantum hilbert scrambling and steganography about the moire´ fringe,” Quantum Engineering, vol. 2023, no. 1, p. 3746357, (2023). [Online]. Available: https://onlinelibrary.wiley.com/doi/abs/10.1155/2023/3746357 [Google Scholar]
  21. Z. Wei, M. Han, H. Yin, and G. Hu, “A quantum color image watermarking protocol based on least significant bit,” in 2024 5th International Conference on Computer Vision, Image and Deep Learning (CVIDL), (2024), pp. 174–179. [Online]. Available: https://ieeexplore.ieee.org/document/10603657 [Google Scholar]
  22. F. Yan and S. E. Venegas-Andraca, Quantum Image Security. Singapore: Springer Singapore, (2020), pp. 79–104. [Online]. Available: https://doi.org/10.1007/978-981-32-9331-14 [Google Scholar]
  23. Z. Wang, M. Xu, and Y. Zhang, “Review of quantum image processing,” Archives of Computational Methods in Engineering, vol. 29, no. 2, pp. 737–761, ( 2022). [Online]. Available: https://doi.org/10.1007/s11831-021-09599-2 [Google Scholar]
  24. A. Anand and A. K. Singh, “An overview on quantum image watermarking for security of covid-19 patient record,” IETE Journal of Research, vol. 0, no. 0, pp. 1–15, (2021). [Online]. Available: https://ieeexplore.ieee.org/document/9778153 [Google Scholar]
  25. W.-W. Hu, R.-G. Zhou, A. El-Rafei, and S.-X. Jiang, “Quantum Image Watermarking Algorithm Based on Haar Wavelet Transform,” IEEE Access, vol. 7, pp. 121 303–121 320, 2019. [Online]. Available: https://inspirehep.net/literature/2706722 [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.