OSA's Digital Library

Journal of the Optical Society of America A

Journal of the Optical Society of America A


  • Vol. 16, Iss. 12 — Dec. 1, 1999
  • pp: 2859–2865

Improved restoration of space object imagery

J. J. Green and B. R. Hunt  »View Author Affiliations

JOSA A, Vol. 16, Issue 12, pp. 2859-2865 (1999)

View Full Text Article

Enhanced HTML    Acrobat PDF (555 KB)

Browse Journals / Lookup Meetings

Browse by Journal and Year


Lookup Conference Papers

Close Browse Journals / Lookup Meetings

Article Tools



We examine methods for preprocessing a collection of atmospheric turbulence-degraded short-exposure imagery to improve the resolving power of estimation algorithms. We redefine the method known as frame selection in the context of optimizing estimation results. We compare several measures of image quality with idealized standards, demonstrating their relative ability to rank highly the least-degraded image frames. In particular, we find the Fisher information measure to be the most noise tolerant and robust frame-selection measure. We then examine the resolving implication of removing additive background noise resulting from the sky and telescope. Specifically, we show that background compensation acts as a de facto restoration of the compact object support and leads to furthering the resolving power of estimation methods. Results from simulated imaging scenarios demonstrate the improved ability of a multiframe maximum a posteriori estimator to restore the passband object distribution as well as to further recover the lost spectral content residing beyond the diffraction limit.

© 1999 Optical Society of America

OCIS Codes
(100.1830) Image processing : Deconvolution
(100.2000) Image processing : Digital image processing
(100.3020) Image processing : Image reconstruction-restoration
(100.3190) Image processing : Inverse problems
(100.6640) Image processing : Superresolution

Original Manuscript: February 10, 1999
Revised Manuscript: August 11, 1999
Manuscript Accepted: August 11, 1999
Published: December 1, 1999

J. J. Green and B. R. Hunt, "Improved restoration of space object imagery," J. Opt. Soc. Am. A 16, 2859-2865 (1999)

Sort:  Author  |  Year  |  Journal  |  Reset  


  1. H. C. Andrews, B. R. Hunt, Digital Image Restoration (Prentice-Hall, Englewood Cliffs, N.J., 1977).
  2. D. G. Sheppard, B. R. Hunt, M. W. Marcellin, “Iterative multiframe superresolution algorithms for atmospheric turbulence-degraded imagery,” J. Opt. Soc. Am. A 15, 978–992 (1998). [CrossRef]
  3. B. R. Hunt, P. J. Sementilli, “Description of a Poisson imagery super-resolution algorithm,” in Astronomical Data Analysis Software and Systems I, D. Worral, C. Biemesderfer, J. Barnes, eds. (Astronomy Society of the Pacific, San Francisco, Calif., 1992), pp. 196–199.
  4. B. R. Hunt, “Super-resolution of images: algorithms, principles, performance,” Int. J. Imaging Syst. Technol. 6, 297–304 (1991). [CrossRef]
  5. D. L. Fried, “Probability of getting a lucky short-exposure image through turbulence,” J. Opt. Soc. Am. 68, 1651–1658 (1978). [CrossRef]
  6. J. C. Christou, D. W. McCarthy, M. L. Cobb, “Image selection and binning for improved atmospheric calibration of infrared speckle data,” Astron. J. 94, 516–522 (1987). [CrossRef]
  7. R. A. Muller, A. Buffington, “Real-time correction of atmospherically degraded telescope images through image sharpening,” J. Opt. Soc. Am. 64, 1200–1210 (1974). [CrossRef]
  8. M. C. Roggemann, C. A. Stoudt, B. M. Welsh, “Image-spectrum signal-to-noise ratio improvements by statistical frame selection for adaptive-optics imaging through atmospheric turbulence,” Opt. Eng. 33, 3254–3264 (1994). [CrossRef]
  9. S. D. Ford, M. C. Roggemann, B. M. Welsh, “Frame selection performance limits for statistical image reconstruction of adaptive optics compensated images,” Opt. Eng. 35, 1025–1034 (1996). [CrossRef]
  10. J. W. Goodman, Introduction to Fourier Optics (McGraw-Hill, New York, 1968).
  11. D. G. Sheppard, B. R. Hunt, M. W. Marcellin, “Iterative multiframe super-resolution algorithms for atmospheric turbulence-degraded imagery,” in Proceedings of the International Conference on Acoustics, Speech, and Signal Processing (Institute of Electrical and Electronics Engineers, Piscataway, N.J., 1998), pp. 2857–2860.
  12. J. J. Green, B. R. Hunt, “Super-resolution in a synthetic aperture imaging system,” in Proceedings of the International Conference on Image Processing (IEEE Computer Society Press, Los Alamitos, Calif., 1997), pp. 865–868.
  13. B. R. Frieden, Probability, Statistical Optics, and Data Testing (Springer-Verlag, Berlin, 1991).
  14. B. R. Frieden, Physics from Fisher Information (Cambridge U. Press, Cambridge, UK, 1998).
  15. H. L. Van Trees, Detection, Estimation, and Modulation Theory (Wiley, New York, 1968).
  16. D. Kincaid, W. Cheney, Numerical Analysis (Brooks/Cole, Pacific Grove, Calif., 1991).
  17. M. R. Banham, A. K. Katsaggelos, “Digital image restoration,” IEEE Signal Process. Lett. 14, 24–41 (1997). [CrossRef]
  18. P. J. Sementilli, M. S. Nadar, B. R. Hunt, “Analysis of the limit to superresolution in incoherent imaging,” J. Opt. Soc. Am. A 10, 2265–2276 (1993). [CrossRef]
  19. M. S. Nadar, “Minimum cross-entropy formulations in image super-resolution,” Ph.D. dissertation (University of Arizona, Tucson, Az., 1996).
  20. A. V. Oppenheim, R. W. Schafer, Discrete-Time Signal Processing (Prentice-Hall, Englewood Cliffs, N.J., 1989).

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