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Applied Optics

Applied Optics

APPLICATIONS-CENTERED RESEARCH IN OPTICS

  • Vol. 37, Iss. 21 — Jul. 20, 1998
  • pp: 4614–4622

Myopic deconvolution of adaptive optics images by use of object and point-spread function power spectra

Jean-Marc Conan, Laurent M. Mugnier, Thierry Fusco, Vincent Michau, and Gérard Rousset  »View Author Affiliations


Applied Optics, Vol. 37, Issue 21, pp. 4614-4622 (1998)
http://dx.doi.org/10.1364/AO.37.004614


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Abstract

Adaptive optics systems provide a real-time compensation for atmospheric turbulence. However, the correction is often only partial, and a deconvolution is required for reaching the diffraction limit. The need for a regularized deconvolution is discussed, and such a deconvolution technique is presented. This technique incorporates a positivity constraint and some a priori knowledge of the object (an estimate of its local mean and a model for its power spectral density). This method is then extended to the case of an unknown point-spread function, still taking advantage of similar a priori information on the point-spread function. Deconvolution results are presented for both simulated and experimental data.

© 1998 Optical Society of America

OCIS Codes
(010.1080) Atmospheric and oceanic optics : Active or adaptive optics
(010.1330) Atmospheric and oceanic optics : Atmospheric turbulence
(100.1830) Image processing : Deconvolution
(100.3020) Image processing : Image reconstruction-restoration
(100.3190) Image processing : Inverse problems
(110.6770) Imaging systems : Telescopes

Citation
Jean-Marc Conan, Laurent M. Mugnier, Thierry Fusco, Vincent Michau, and Gérard Rousset, "Myopic deconvolution of adaptive optics images by use of object and point-spread function power spectra," Appl. Opt. 37, 4614-4622 (1998)
http://www.opticsinfobase.org/ao/abstract.cfm?URI=ao-37-21-4614


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References

  1. A. Labeyrie, “Attainment of diffraction-limited resolution in large telescopes by Fourier analysing speckle patterns,” Astron. Astrophys. 6, 85–87 (1970).
  2. K. T. Knox and B. J. Thompson, “Recovery of images from atmospherically degraded short exposure photographs,” Astrophys. J. Lett. 193, L45–L48 (1974).
  3. G. Weigelt, “Modified astronomical speckle interferometry speckle masking,” Opt. Commun. 21, 55–59 (1977).
  4. J. Primot, G. Rousset, and J.-C. Fontanella, “Deconvolution from wavefront sensing: a new technique for compensating turbulence-degraded images,” J. Opt. Soc. Am. A 7, 1598–1608 (1990).
  5. J. W. Hardy, J. E. Lefevbre, and C. L. Koliopoulos, “Real time atmospheric compensation,” J. Opt. Soc. Am. 67, 360–369 (1977).
  6. G. Rousset, J.-C. Fontanella, P. Kern, P. Gigan, F. Rigaut, P. Léna, C. Boyer, P. Jagourel, J.-P. Gaffard, and F. Merkle, “First diffraction-limited astronomical images with adaptive optics,” Astron. Astrophys. 230, L29–L32 (1990).
  7. F. Rigaut, G. Rousset, P. Kern, J.-C. Fontanella, J.-P. Gaffard, F. Merkle, and P. Léna, “Adaptive optics on a 3.6-m telescope: results and performance,” Astron. Astrophys. 250, 280–290 (1991).
  8. M. C. Roggemann and C. L. Matson, “Power spectrum and Fourier phase spectrum estimation by using fully and partially compensating adaptive optics and bispectrum postprocessing,” J. Opt. Soc. Am. A 9, 1525–1535 (1992).
  9. J.-M. Conan, P.-Y. Madec, and G. Rousset, “Image formation in adaptive optics partial correction,” in Active and Adaptive Optics, F. Merkle, ed., Vol. 48 of ESO Conference and Workshop Proceedings (European Southern Observatory, Garching, Germany, 1993), pp. 181–186.
  10. J.-M. Conan, “Étude de la correction partielle en optique adaptative,” Ph.D. thesis (Université de Paris XI, Orsay, France, 1994).
  11. A. K. Jain, Fundamentals of Digital Image Processing (Prentice-Hall, Englewood Cliffs, New Jersey, 1989), Chap. 2.
  12. D. L. Fried, “Statistics of a geometric representation of wavefront distortion,” J. Opt. Soc. Am. 55, 1427–1435 (1965).
  13. A. Tikhonov and V. Arsenin, Solutions of Ill-Posed Problems (Winston, Washington, D.C., 1977).
  14. M. Z. Nashed, “Operator-theoretic and computational approaches to ill-posed problems with applications to antenna theory,” IEEE Trans. Antennas Propag. AP-29, 220–231 (1981).
  15. W. L. Root, “Ill-posedness and precision in object-field reconstruction problems,” J. Opt. Soc. Am. A 4, 171–179 (1987).
  16. D. M. Titterington, “General structure of regularization procedures in image reconstruction,” Astron. Astrophys. 144, 381–387 (1985).
  17. G. Demoment, “Image reconstruction and restoration: overview of common estimation structures and problems,” IEEE Trans. Acoust. Speech Signal Process. 37, 2024–2036 (1989).
  18. B. R. Hunt, “The application of constrained least squares estimation to image restoration by digital computer,” IEEE Trans. Comput. C-22, 805–812 (1973).
  19. W. H. Richardson, “Bayesian-based iterative method of image restoration,” J. Opt. Soc. Am. 62, 55–59 (1972).
  20. L. B. Lucy, “An iterative technique for rectification of observed distributions,” Astrophys. J. 79, 745–754 (1974).
  21. D. L. Phillips, “A technique for the numerical solution of certain integral equations of the first kind,” J. Assoc. Comput. Mach. 9, 84–97 (1962).
  22. A. K. Katsaggelos, ed., Digital Image Restoration, Springer Series in Information Sciences, (Springer-Verlag, Berlin, 1991), Chap. 1.
  23. H. L. Van Trees, Detection, Estimation, and Modulation Theory Part I (Wiley, New York, 1968).
  24. A. Papoulis, Probability, Random Variables, and Stochastic Processes, 3rd ed. (McGraw-Hill, New York, 1991).
  25. B. R. Hunt, “Bayesian methods in nonlinear digital image restoration,” IEEE Trans. Comput. C-26, 219–229 (1977).
  26. J. Nunez and J. Llacer, “A general Bayesian image reconstruction algorithm with entropy prior: preliminary application to HST data,” Publ. Astron. Soc. Pac. 105, 1192–1208 (1993).
  27. A. P. Kattnig and J. Primot, “Model of the second-order statistic of the radiance field of natural scenes, adapted to system conceiving,” in Visual Information Processing VI, S. K. Park and R. D. Juday, eds., Proc. SPIE 3074, 132–141 (1997).
  28. F. O. Huck, R. Alter-Gartenberg, and Z. Rahman, “Image gathering and digital restoration for fidelity and visual quality,” Comput. Vision Graphics Image Process. 53, 71–84 (1991).
  29. E. Thiébaut and J.-M. Conan, “Strict a priori constraints for maximum-likelihood blind deconvolution,” J. Opt. Soc. Am. A 12, 485–492 (1995).
  30. J.-P. Véran, F. Rigaut, and H. Maître, “Adaptive optics long exposure point spread function retrieval from wavefront sensor measurements,” in Adaptive Optics, M. Cullum, ed., Vol. 54 of ESO Conference and Workshop Proceedings (European Southern Observatory, Garching, Germany, 1995), pp. 497–502.
  31. J.-P. Véran, F. Rigaut, H. Maître, and D. Rouan, “Estimation of the adaptive optics long-exposure point-spread function using control loop data,” J. Opt. Soc. Am. A 14, 3057–3069 (1997).
  32. G. R. Ayers and J. C. Dainty, “Iterative blind deconvolution and its applications,” Opt. Lett. 13, 547–549 (1988).
  33. R. W. Gerchberg and W. O. Saxton, “A practical algorithm for the determination of phase from image and diffraction plane pictures,” Optik 35, 237–246 (1972).
  34. R. W. Gerchberg, “Super-resolution through error energy reduction,” Opt. Acta 21, 709–720 (1974).
  35. A. Papoulis, “A new algorithm in spectral analysis and band-limited extrapolation,” IEEE Trans. Circuits Syst. CS-22, 735 (1975).
  36. A. Levi and H. Stark, “Restoration from phase and magnitude by generalized projections,” in Image Recovery: Theory and Application, H. Stark, ed. (Academic, New York, 1987), Chap. 8, pp. 277–320.
  37. T. J. Holmes, “Blind deconvolution of speckle images quantum-limited incoherent imagery: maximum-likelihood approach,” J. Opt. Soc. Am. A 9, 1052–1061 (1992).
  38. R. G. Lane, “Blind deconvolution of speckle images,” J. Opt. Soc. Am. A 9, 1508–1514 (1992).
  39. T. J. Schultz, “Multiframe blind deconvolution of astronomical images,” J. Opt. Soc. Am. A 10, 1064–1073 (1993).
  40. S. M. Jefferies and J. C. Christou, “Restoration of astronomical images by iterative blind deconvolution,” Astrophys. J. 415, 862–874 (1993).
  41. R. G. Lane, “Methods for maximum-likelihood deconvolution,” J. Opt. Soc. Am. A 13, 1992–1998 (1996).
  42. J. C. Christou, D. Bonaccini, and N. Ageorges, “Deconvolution of adaptive optics near-infrared system (ADONIS) images,” in Adaptive Optics and Applications, R. K. Tyson and R. Q. Fugate, eds., Proc. SPIE 3126, 68–80 (1997).
  43. Y.-L. You and M. Kaveh, “A regularization approach to joint blur identification and image restoration,” IEEE Trans. Image Process. 5, 416–428 (1996).
  44. J. C. Dainty and A. H. Greenaway, “Estimation of spatial power spectra in speckle interferometry,” J. Opt. Soc. Am. A 69, 786–790 (1979).
  45. J. W. Goodman, Statistical Optics (Wiley-Interscience, New York, 1985), Chap. 8.
  46. P. Y. Madec, D. Rabaud, B. Fleury, J. M. Conan, L. Rousset-Rouvière, F. Mendez, J. Montri, V. Michau, G. Rousset, and M. Séchaud, “Essais du banc d’optique adaptative ONERA à l’OHP,” Lett. Observatoire de Haute Provence 16, 2–3 (1997).
  47. C. Dumas and O. R. Hainaut, “Mapping Vesta in the visible and near-infrared: the 1994 and 1996 oppositions as viewed from the ground,” in Evolution of Igneous Asteroids: Focus on Vesta and the HED Meteorites, D. W. Mittlefehldt and J. J. Papike, eds., Lunar and Planetary Institute Tech. Rep. 96–02(1) (Lunar and Planetary Institute, Houston, Tex., 1996), pp. 7–8.
  48. C. Dumas and O. R. Hainaut, “Mapping Vesta with adaptive optics: the 1996 opposition,” Bull. Am. Astron. Soc. 28, 1101 (1996).

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