OSA's Digital Library

Journal of the Optical Society of America A

Journal of the Optical Society of America A


  • Editor: Franco Gori
  • Vol. 31, Iss. 4 — Apr. 1, 2014
  • pp: 794–801

Improving night sky star image processing algorithm for star sensors

Mohammad Vali Arbabmir, Seyyed Mohammad Mohammadi, Sadegh Salahshour, and Farshad Somayehee  »View Author Affiliations

JOSA A, Vol. 31, Issue 4, pp. 794-801 (2014)

View Full Text Article

Enhanced HTML    Acrobat PDF (535 KB)

Browse Journals / Lookup Meetings

Browse by Journal and Year


Lookup Conference Papers

Close Browse Journals / Lookup Meetings

Article Tools



In this paper, the night sky star image processing algorithm, consisting of image preprocessing, star pattern recognition, and centroiding steps, is improved. It is shown that the proposed noise reduction approach can preserve more necessary information than other frequently used approaches. It is also shown that the proposed thresholding method unlike commonly used techniques can properly perform image binarization, especially in images with uneven illumination. Moreover, the higher performance rate and lower average centroiding estimation error of near 0.045 for 400 simulated images compared to other algorithms show the high capability of the proposed night sky star image processing algorithm.

© 2014 Optical Society of America

OCIS Codes
(100.0100) Image processing : Image processing
(120.0120) Instrumentation, measurement, and metrology : Instrumentation, measurement, and metrology
(150.0150) Machine vision : Machine vision

ToC Category:
Image Processing

Original Manuscript: October 3, 2013
Revised Manuscript: February 15, 2014
Manuscript Accepted: February 16, 2014
Published: March 27, 2014

Mohammad Vali Arbabmir, Seyyed Mohammad Mohammadi, Sadegh Salahshour, and Farshad Somayehee, "Improving night sky star image processing algorithm for star sensors," J. Opt. Soc. Am. A 31, 794-801 (2014)

Sort:  Author  |  Year  |  Journal  |  Reset  


  1. H. Liu, J. Yang, J. Wang, J. Tan, and X. Li, “Star spot location estimation using Kalman filter for star tracker,” Appl. Opt. 50, 1735–1744 (2011). [CrossRef]
  2. R. Berry and J. Burnell, The Handbook of Astronomical Image Processing, 2nd ed. (Willmann-Bell, 2005).
  3. K. M. Huffman, “Designing star trackers to meet micro-satellite requirements,” Master’s thesis (Massachusetts Institute of Technology, 2006).
  4. S. B. Howell, Handbook of CCD Astronomy (Cambridge University, 2006).
  5. Y. Hayosang, “A star recognition algorithm on dynamic environment,” Master’s thesis (KAIST, 2010).
  6. Q. Wei and Z. Weina, “Restoration of motion-blurred star image based on Wiener filter,” in Fourth International Conference on Intelligent Computation Technology and Automation, Shenzhen, Guangdong (2011).
  7. M. A. Samaan, “Toward faster and more accurate star sensors using recursive centroiding and star identification,” Ph.D. dissertation (Texas A&M University, 2003).
  8. R. C. Gonzalez and R. E. Woods, Digital Image Processing, 3rd ed. (Prentice-Hall, 2008).
  9. P. D. Wellner, “Adaptive thresholding for the digitaldesk,” (EuroPARC, 1993).
  10. N. Ma, D. G. Bailey, and C. T. Johnston, “Optimised single pass connected components analysis,” in IEEE International Conference on Field Programmable Technology, Taipei (2008).
  11. K. Suzuki, I. Horiba, and N. Sugieb, “Linear-time connected-component labeling based on sequential local operations,” Comput. Vis. Image Underst. 89, 1–23 (2003). [CrossRef]
  12. R. Walczyk, A. Armitage, and T. D. Binnie, “Comparative study on connected component labeling algorithms for embedded video processing systems,” in Proceedings of the 2010 International Conference on Image Processing, Computer Vision, and Pattern Recognition (IPCV) (CSREA, 2010).
  13. R. Haralick, “Some neighborhood operations,” in Real Time Parallel Computing: Image Analysis (Plenum, 1981), pp. 11–35.
  14. D. Bailey and C. Johnston, “Single pass connected components analysis,” in Proceedings of Image and Vision ComputingHamilton, New Zealand (2008), pp. 282–287.
  15. A. Vyas, M. B. Roopashree, and B. R. Prasad, “Performance of centroiding algorithms at low light level conditions in adaptive optics,” in International Conference on Advances in Recent Technologies in Communication and Computing, Kerala, India (2009).
  16. M. Knutson and D. Miller, “Fast star tracker centroid algorithm for high performance CubeSat with air bearing validation,” Master’s thesis (Massachusetts Institute of Technology, 2012).
  17. M. Kolomenkin, S. Polak, I. Shimshoni, and M. Lindenbaum, “Geometric voting algorithm for star trackers,” IEEE Trans. Aerosp. Electron. Syst. 44, 441–456 (2008). [CrossRef]
  18. C. Fosu, G. W. Hei, and B. Eissfeller, “Determination of centroid of CCD star images,” Int. Arch. Photogram. Remote Sens. Spatial Inform. Sci. 35, 612–617 (2004).
  19. F. Wu, W. Shen, J. Zhou, and X. Chen, “Design and simulation of a novel APS star tracker,” in International Conference on Optical Instruments and Technology: Optical Systems and Optoelectronic Instruments (2008).
  20. J. Shen, G. Zhang, and X. Wei, “Simulation analysis of dynamic working performance for star trackers,” J. Opt. Soc. Am. A 27, 2638–2647 (2010). [CrossRef]
  21. S. M. Mohammadi, M. S. Helfroush, and K. Kazemi, “Novel shape-texture feature extraction for medical x-ray image classification,” Int. J. Innovative Comput. Inform. Control 8, 659–676 (2012).
  22. B. M. Quine, V. Tarasyuk, H. Mebrahtu, and R. Hornsey, “Determining star-image location: a new sub-pixel interpolation technique to process image centroids,” Comput. Phys. Commun. 177, 700–706 (2007). [CrossRef]

Cited By

Alert me when this paper is cited

OSA is able to provide readers links to articles that cite this paper by participating in CrossRef's Cited-By Linking service. CrossRef includes content from more than 3000 publishers and societies. In addition to listing OSA journal articles that cite this paper, citing articles from other participating publishers will also be listed.

« Previous Article  |  Next Article »

OSA is a member of CrossRef.

CrossCheck Deposited