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Dynamic image stabilization precision test system based on the Hessian matrix

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Abstract

Dynamic image stabilization precision of an optical image-stable device is a key technical indicator. Therefore, a fast dynamic image stabilization precision test system for an optical image-stable device is developed. A large-aperture collimator with a designed cross divisional board is used to simulate the infinity goal. The image-stable device is installed on the motion simulator with six degrees of freedom which is used to simulate the moving state of the device. The CCD camera installed behind the eyepiece lens of the image-stable device acquires images rapidly and in real time. The local energy maxima center of the cross light spot can be acquired accurately through the proposed algorithm using the Hessian matrix. In addition, to deal with the CCD non-uniformity, an adaptive non-uniformity correction algorithm based on bi-dimensional empirical mode decomposition is provided. The actual test results for the proposed method show that the test error of dynamic image stabilization is less than 0.7″, and the time for the frame image acquisition and processing is less than 10 ms, which demonstrates the effectiveness of the test system.

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References

  1. Wang Z D, Wang C Y. The stable precision measurement device design for gun system. J Changchun Univ Sci Tec (Nat Sci Ed), 2008, 31: 68–70

    Google Scholar 

  2. Li J X, Zhou G C, Yi Q. Design of image-capturing system measuring Z axis of sighting mirror. J Acad Armored Force Eng, 2006, 20: 31–33

    Google Scholar 

  3. Zhou G C, Li J X. Method of image measuring on the deviation of lower reflection image-stabilization. J Acad Armored Force Eng, 2007, 21: 70–77

    Google Scholar 

  4. Guru D, Shekar B, Nagabhashan P. A simple and robust line detection algorithm based on small eigenvalue analysis. Patt Recog Lett, 2004, 25: 1–13

    Article  Google Scholar 

  5. Chen T, Chung K. A new randomized algorithm for detecting lines. Real-Time Imag, 2001, 7: 473–481

    Article  MATH  Google Scholar 

  6. Liu F. Research on the laser calibration method for the image plane center of the visual sensor. Lecture Notes Control Inf Sci, 2007, 362: 295–302

    Article  Google Scholar 

  7. Li W M, Yu Q Y, Hu H Z, et al. Iteration algorithm of surface fitting in the detection of light-spot position. Opt Tech, 2004, 30: 33–35

    Google Scholar 

  8. Zhang G J. Vision Measurement. Beijing: Science Press, 2008

    Google Scholar 

  9. Wei Z Z, Gao M, Zhang G J, et al. Sub-pixel extraction method for the center of light-spot image. Opto-Electr Eng, 2009, 36: 7–12

    Google Scholar 

  10. Wei P, Zhu Y Y, Liu C, et al. Non-uniformity correction for SLM microscopic images. Image Vision Comput, 2009, 27: 782–789

    Article  Google Scholar 

  11. Sergio K, Torres S N. Real-time Kalman filtering for non-uniformity correction on infrared image sequences: Performance and analysis. Lecture Notes Comput Sci, 2005, 3773: 752–761

    Article  Google Scholar 

  12. Zhou H X, Qin H L, Jian Y B, et al. Improved Kalman-filter non-uniformity correction algorithm for infrared focal plane arrays. Infrared Phys Tech, 2008, 51: 528–531

    Article  Google Scholar 

  13. Friedenberg A, Goldblatt I. Non-uniformity two-point linear correction errors in infrared focal plane arrays. Opt Eng, 1998, 37: 1251–1253

    Article  Google Scholar 

  14. Wang L, Wang S Y, Zhou H. Basic principles and use method of collimator. Chin J Sci Instrum, 2006, 27: 980–982

    Google Scholar 

  15. Quine B M, Tarasyuk V, Mebrahtu H, et al. Determining star-image location: A new sub-pixel interpolation technique to process image centroids. Comput Phys Commun, 2007, 177: 700–706

    Article  MATH  Google Scholar 

  16. Zhang X D. Matrix Analysis and Applications. Beijing: Tsinghua University Press, 2008

    Google Scholar 

  17. Chen K, Wang Y C, Yang R N. Hessian matrix based saddle point detection for granules segmentation in 2D image. J Electr, 2008, 25: 728–736

    Google Scholar 

  18. Hermosilla T, Bermejo E, Balaguerb A, et al. Nonlinear fourth-order image interpolation for subpixel edge detection and localization. Image Vision Comput, 2008, 26: 1240–1248

    Article  Google Scholar 

  19. Liu Y X, Hao Z H. Research on the non-uniformity correction of linear TDI CCD remote camera. Advanced Materials and Devices for Sensing and Imaging II. Proc SPIE. 2005, 5633: 527–535

    Article  Google Scholar 

  20. de Lasarte M, Pujol J, Arjona M, et al. Optimized algorithm for the spatial non-uniformity correction of an imaging system based on a charge-coupled device color camera. Appl Opt, 2007, 46: 167–174

    Article  Google Scholar 

  21. Huang N E, Shen Z, Long S R, et al. The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis. Proc Royal Society of London, Ser A, 1998, 454: 903–995

    Article  MathSciNet  MATH  Google Scholar 

  22. Li H, Xu S H, Li L Q. Dim target detection and tracking based on empirical mode decomposition. Sig Process Image Commun, 2008, 23: 788–797

    Article  Google Scholar 

  23. Liu Z X, Peng S L. Boundary processing of bidimensional EMD using texture synthesis. IEEE Sig Process Lett, 2005, 12: 33–36

    Article  Google Scholar 

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Authors and Affiliations

  1. Key Laboratory of Complex System Intelligent Control and Decision, School of Automation, Beijing Institute of Technology, Beijing, 100081, China

    Jing Li, JunZheng Wang, ShouKun Wang, LiLing Ma & Wei Shen

Authors
  1. Jing Li
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  2. JunZheng Wang
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  3. ShouKun Wang
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  4. LiLing Ma
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  5. Wei Shen
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Correspondence to Jing Li.

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Li, J., Wang, J., Wang, S. et al. Dynamic image stabilization precision test system based on the Hessian matrix. Sci. China Inf. Sci. 55, 2056–2074 (2012). https://doi.org/10.1007/s11432-011-4290-z

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  • DOI: https://doi.org/10.1007/s11432-011-4290-z

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