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Strategy for quantum image stabilization

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Abstract

Image stabilization is a process to smooth the unstable motion vector of video sequences to achieve its stabilization. Even though the classical image stabilization techniques seem already very mature so far, similar advances have not been extended to the quantum computing domain. In this study, we explore a novel quantum video framework and make a modest attempt to perform the image stabilization based on it by utilizing the quantum comparator and quantum image translation operations. The proposed method is capable of estimating the camera motion during exposure and compensating for the video jitter caused by the motion. In addition, the quantum properties, i.e., entanglement and parallelism, ensure that the quantum image stabilization is feasible and effective. Finally, a simple experiment to stabilize a four-frame jittered quantum video is implemented using Matlab based on linear algebra with complex vectors as quantum states and unitary matrices as unitary transforms to show the feasibility and merits of this proposal.

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References

  1. Ji H X, Li B A, Yao J. Electronic image stabilization algorithm based on TD filter. In: Proceedings of the 4th International Congress on Image and Signal Processing, Shanghai, 2011. 682–686

    Google Scholar 

  2. Liu J, Shi C C. Image stabilization based on BM-EMD. In: Proceedings of IEEE 3rd International Conference on Communication Software and Networks, Xi’an, 2011. 591–593

    Google Scholar 

  3. Zhu J J. Research on theory and application of electronic image stabilization. Dissertation for the Doctoral Degree, Xidian University, 2009

    Google Scholar 

  4. Zhang H L, Wu Q, Liu T Q, et al. Design and implementation of electronic image stabilization system based on dual-core DSP. In: Proceedings of the 9th International Conference on Intelligent Information Hiding and Multimedia Signal Processing, Beijing, 2013. 117–120

    Google Scholar 

  5. Xu L D, Lin X G. Digital image stabilization based on circular block matching. IEEE Trans Consumer Electron, 2006, 52: 566–574

    Article  Google Scholar 

  6. Tico M. Adaptive block-based approach to image stabilization. In: Proceedings of the 15th IEEE International Conference on Image Processing, San Diego, 2008. 521–524

    Google Scholar 

  7. Jia R M, Zhang H, Wang L, et al. Digital image stabilization based on phase correlation. In: Proceedings of the International Conference on Artificial Intelligence and Computational Intelligence, Shanghai, 2009. 485–489

    Google Scholar 

  8. Sanjeev K, Azartash H, Biswas M, et al. Real-time affine gloabal motion estimation using phase correlation and its application for digital image stabilization. IEEE Trans Image Process, 2011, 20: 3406–3418

    Article  MathSciNet  Google Scholar 

  9. Tico M, Vehvilainen M. Image stabilization based on fusing the visual information in differently exposed images. In: Proceedings of the IEEE International Conference on Image Processing, San Antonio, 2007. 117–120

    Google Scholar 

  10. Smith M J, Boxerbaum A, Peterson G L, et al. Electronic image stabilization using optical flow with inertial fusion. In: Proceedings of the IEEE International Conference on Intelligent Robots and Systems, Taipei, 2010. 1146–1153

    Google Scholar 

  11. Dai W C, Lu Y, Zhu J, et al. An integrated quantum secure communication system. Sci China Inf Sci, 2011, 54: 2578–2591

    Article  MathSciNet  Google Scholar 

  12. Nielsen M A, Chuang I L. Quantum Computation and Quantum Information. Cambridge: Cambridge University Press, 2010

    Book  MATH  Google Scholar 

  13. Yan F, Iliyasu A M, Jiang Z G. Quantum computation-based image representation, processing operations and their applications. Entropy, 2014, 16: 5290–5338

    Article  MathSciNet  Google Scholar 

  14. Yan F, Iliyasu A M, Venegas-Andraca S E. A survey of quantum image representations. Quantum Inf Process, 2016, 15: 1–35

    Article  MathSciNet  MATH  Google Scholar 

  15. Hu B Q, Huang X D, Zhou R G, et al. A theoretical framework for quantum image representation and data loading scheme. Sci China Inf Sci, 2014, 57: 032108

    MATH  Google Scholar 

  16. Venegas-Andraca S E, Bose S. Storing, processing, and retrieving an image using quantum mechanics. In: Proceedings of SPIE Conference of Quantum Information and Computation. Bellingham: SPIE, 2003. 134–147

    Google Scholar 

  17. Yan F, Iliyasu A M, Sun B, et al. A duple watermarking strategy for multi-channel quantum images. Quantum Inf Process, 2015, 14: 1675–1692

    Article  MathSciNet  MATH  Google Scholar 

  18. Zhang Y, Lu K, Gao Y H. QSobel: a novel quantum image edge extraction algorithm. Sci China Inf Sci, 2015, 58: 012106

    MATH  Google Scholar 

  19. Yan F, Iliyasu A M, Le P Q, et al. A parallel comparison of multiple pairs of images on quantum computers. Int J Innovat Comput Appl, 2013, 5: 199–212

    Article  Google Scholar 

  20. Yan F, Iliyasu A M, Fatichah C, et al. Quantum image searching based on probability distributions. J Quantum Inf Sci, 2012, 2: 55–60

    Article  Google Scholar 

  21. Bhargava B, Shi C G, Wang S Y. Mpeg video encryption algorithms. Multimedia Tool Appl, 2004, 24: 57–79

    Article  Google Scholar 

  22. Iliyasu A M, Le P Q, Dong F Y, et al. A framework for representing and producing movies on quantum computers. Int J Quantum Inf, 2011, 9: 1459–1497

    Article  MATH  Google Scholar 

  23. Le P Q, Dong F Y, Hirota K. A flexible representation of quantum images for polynomial preparation, image compression, and processing operations. Quantum Inf Process, 2011, 10: 63–84

    Article  MathSciNet  MATH  Google Scholar 

  24. Sun B, Le P Q, Iliyasu A M, et al. A multi-channel representation for images on quantum computers using the RGBa color space. In: Proceedings of IEEE 7th International Symposium on Intelligent Signal Processing (WISP), Floriana, 2011. 827–834

    Google Scholar 

  25. Yan F, Iliyasu A M, Venegas-Andraca S E, et al. Video encryption and decryption on quantum computers. Int J Theor Phys, 2015, 54: 2893–2904

    Article  MathSciNet  MATH  Google Scholar 

  26. Yan F, Iliyasu A M, Khan A R, et al. Moving target detection in multi-channel quantum video. In: Proceedings of IEEE 9th International Symposium on Intelligent Signal Processing (WISP), Siena, 2015. 1–5

    Google Scholar 

  27. Zhang Y, Lu K, Gao Y H, et al. NEQR: a novel enhanced quantum representation of digital images. Quantum Inf Process, 2013, 12: 2833–2860

    Article  MathSciNet  MATH  Google Scholar 

  28. Vedral V V, Barenco A, Ekert A. Quantum networks for elementary arithmetic operations. Phys Rev A, 1996, 54: 147–153

    Article  MathSciNet  Google Scholar 

  29. Wang D, Liu Z H, Zhu W N, et al. Design of quantum comparator based on extended general toffoli gates with multiple targets. Comput Sci, 2012, 39: 302–306

    Google Scholar 

  30. Le Z X. Digital Image Information Processing. Beijing: National Defence Industry Press, 2003

    Google Scholar 

  31. Wang J, Jiang N, Wang L. Quantum image translation. Quantum Inf Process, 2015, 14: 1589–1604

    Article  MathSciNet  MATH  Google Scholar 

  32. Zhang Y, Lu K, Gao Y H, et al. A novel quantum representation for log-polar images. Quantum Inf Process, 2013, 12: 3103–3126

    Article  MathSciNet  MATH  Google Scholar 

  33. Jiang N, Wang L. Quantum image scaling using nearest neighbor interpolation. Quantum Inf Process, 2015, 14: 1559–1571

    Article  MathSciNet  MATH  Google Scholar 

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Authors and Affiliations

  1. School of Computer Science and Technology, Changchun University of Science and Technology, Changchun, 130022, China

    Fei Yan & Huamin Yang

  2. College of Engineering, Prince Sattam Bin Abdulaziz University, Al-Kharj, 11942, KSA

    Abdullah M. Iliyasu

  3. Department of Computational Intelligence and Systems Science, Tokyo Institute of Technology, Yokohama, 2268502, Japan

    Kaoru Hirota

Authors
  1. Fei Yan
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  2. Abdullah M. Iliyasu
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  3. Huamin Yang
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  4. Kaoru Hirota
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Correspondence to Fei Yan.

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Yan, F., Iliyasu, A.M., Yang, H. et al. Strategy for quantum image stabilization. Sci. China Inf. Sci. 59, 052102 (2016). https://doi.org/10.1007/s11432-016-5541-9

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  • DOI: https://doi.org/10.1007/s11432-016-5541-9

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