OSA's Digital Library

Applied Optics

Applied Optics

APPLICATIONS-CENTERED RESEARCH IN OPTICS

  • Vol. 37, Iss. 26 — Sep. 10, 1998
  • pp: 6240–6246

Improved Restoration from Multiple Images of a Single Object: Application to Fluorescence Microscopy

Peter J. Verveer and Thomas M. Jovin  »View Author Affiliations


Applied Optics, Vol. 37, Issue 26, pp. 6240-6246 (1998)
http://dx.doi.org/10.1364/AO.37.006240


View Full Text Article

Acrobat PDF (230 KB)





Browse Journals / Lookup Meetings

Browse by Journal and Year


   


Lookup Conference Papers

Close Browse Journals / Lookup Meetings

Article Tools

Share
Citations

Abstract

We present an approach for the combined restoration of multiple different images of a single object. A linear Tikhonov filter adapted for this purpose is derived in detail. Nonlinear constrained algorithms can also be adapted, and we illustrate this possibility for an iterative constrained Tikhonov algorithm. Both the linear and the iterative constrained Tikhonov algorithms were used to analyze performance in fluorescence confocal imaging by use of simulated and experimental data. One can improve the quality of restored confocal images significantly if the signal that normally is rejected by the detection pinhole of a confocal laser scanning microscope is also recorded on a separate detector such that the two recorded signals are used together for image restoration according to the proposed algorithms.

© 1998 Optical Society of America

OCIS Codes
(000.1430) General : Biology and medicine
(100.1830) Image processing : Deconvolution
(100.3020) Image processing : Image reconstruction-restoration
(100.6890) Image processing : Three-dimensional image processing
(110.0180) Imaging systems : Microscopy
(110.4190) Imaging systems : Multiple imaging

Citation
Peter J. Verveer and Thomas M. Jovin, "Improved Restoration from Multiple Images of a Single Object: Application to Fluorescence Microscopy," Appl. Opt. 37, 6240-6246 (1998)
http://www.opticsinfobase.org/ao/abstract.cfm?URI=ao-37-26-6240


Sort:  Author  |  Year  |  Journal  |  Reset

References

  1. C. J. R. Sheppard, “The spatial frequency cut-off in three-dimensional imaging,” Optik (Stuttgart) 72, 131–133 (1986).
  2. C. J. R. Sheppard, “The spatial frequency cut-off in three-dimensional imaging II,” Optik (Stuttgart) 74, 128–129 (1986).
  3. C. J. R. Sheppard, “Axial resolution of confocal fluorescence microscopy,” J. Microsc. 154, 237–241 (1989).
  4. C. J. R. Sheppard and M. Gu, “The significance of 3-D transfer functions in confocal scanning microscopy,” J. Microsc. 165, 377–390 (1992).
  5. D. A. Agard, Y. Hiraoka, P. Shaw, and J. W. Sedat, “Fluorescence microscopy in three dimensions,” Meth. Cell Biol. 30, 353–377 (1989).
  6. W. A. Carrington, R. M. Lynch, E. D. W. Moore, G. Isenberg, K. E. Fogarty, and F. S. Fay, “Superresolution three-dimensional images of fluorescence in cells with minimal light exposure,” Science 268, 1483–1487 (1995).
  7. T. J. Holmes, “Maximum-likelihood image restoration adapted for noncoherent optical imaging,” J. Opt. Soc. Am. A 5, 666–673 (1988).
  8. T. J. Holmes, S. Bhattacharyya, J. A. Cooper, D. Hanzel, V. Krishnamurthi, W.-C. Lin, B. Roysam, D. H. Szarowski, and J. N. Turner, “Light microscopic images reconstructed by maximum likelihood deconvolution,” in Handbook of Biological Confocal Microscopy, 2nd ed., J. B. Pawley, ed. (Plenum, New York, 1995), Chap. 24, pp. 389–402.
  9. S. Joshi and M. I. Miller, “Maximum a posteriori estimation with Good’s roughness for three-dimensional optical-sectioning microscopy,” J. Opt. Soc. Am. A 10, 1078–1085 (1993).
  10. T. Wilson, “Optical sectioning in confocal fluorescent microscopes,” J. Microsc. 154, 143–156 (1989).
  11. J.-A. Conchello and E. W. Hansen, “Enhanced 3-D reconstruction from confocal scanning microscope images. 1: deterministic and maximum likelihood reconstructions,” Appl. Opt. 29, 3795–3804 (1990).
  12. H. T. M. van der Voort and K. C. Strasters, “Restoration of confocal images for quantitative image analysis,” J. Microsc. 178, 165–181 (1995).
  13. M. Schrader, S. W. Hell, and H. T. M. van der Voort, “Potential of confocal microscopes to resolve in the 50–100-nm range,” Appl. Phys. Lett. 69, 3644–3646 (1996).
  14. G. M. P. van Kempen, L. J. van Vliet, P. J. Verveer, and H. T. M. van der Voort, “A quantitative comparison of image restoration methods for confocal microscopy,” J. Microsc. 185, 354–365 (1997).
  15. P. J. Verveer, Q. S. Hanley, P. W. Verbeek, L. J. van Vliet, and T. M. Jovin, “Theory of confocal fluorescence imaging in the programmable array microscope (PAM),” J. Microsc. 189, 192–198 (1998).
  16. Q. S. Hanley, P. J. Verveer, and T. M. Jovin, “Optical sectioning fluorescence spectroscopy in a programmable array microscope (PAM),” Appl. Spectrosc. 52, 783–789 (1998).
  17. P. J. Verveer and T. M. Jovin, “Efficient superresolution restoration algorithms using maximum a posteriori estimations with application to fluorescence microscopy,” J. Opt. Soc. Am. A 14, 1696–1706 (1997).
  18. P. J. Verveer and T. M. Jovin, “Efficient image restoration based on Good’s roughness penalty with application to fluorescence microscopy,” J. Opt. Soc. Am. A 15, 1077–1083 (1998).
  19. D. L. Snyder, T. J. Schulz, and J. A. O’Sullivan, “Deblurring subject to nonnegativity constraints,” IEEE Trans. Signal Process. 40, 1143–1150 (1992).
  20. I. Csiszár, “Why least squares and maximum entropy? An axiomatic approach to inference for linear inverse problems,” Ann. Statist. 19, 2032–2066 (1991).
  21. P. J. Verveer, G. M. P. van Kempen, and T. M. Jovin, “Super-resolution MAP algorithms applied to fluorescence imaging,” in Three-Dimensional Microscopy: Image Acquisition and Processing IV, C. J. Cogswell, J.-A. Conchello, and T. Wilson, eds., Proc. SPIE 2984, 125–135 (1997).
  22. P. J. Verveer and T. M. Jovin, “Acceleration of the ICTM image restoration algorithm,” J. Microsc. 188, 191–195 (1997).
  23. A. N. Tikhonov and V. Y. Arsenin, Solutions of Ill-Posed Problems (Wiley, New York, 1977).
  24. W. A. Carrington, “Image restoration in 3D microscopy with limited data,” in Bioimaging and Two-Dimensional Spectroscopy, L. C. Smith, ed., Proc. SPIE 1205, 72–83 (1990).
  25. G. H. Golub, M. Heath, and G. Wahba, “Generalized cross-validation as a method for choosing a good ridge parameter,” Technometrics 21, 215–223 (1979).
  26. N. P. Galatsanos and A. K. Katsaggelos, “Methods for choosing the regularization parameter and estimating the noise variance in image restoration and their relation,” IEEE Trans. Image Process. 1, 322–336 (1992).
  27. W. H. Press, S. A. Teukolsky, and W. T. Vetterling, Numerical Recipes in C, 2nd ed. (Cambridge U. Press, Cambridge, 1992).
  28. H. T. M. van der Voort and G. J. Brakenhoff, “3-D image formation in a high-aperture fluorescence confocal microscope: a numerical analysis,” J. Microsc. 158, 43–54 (1990).
  29. A. K. Jain, Fundamentals of Digital Image Processing (Prentice Hall, Englewood Cliffs, N.J., 1989).
  30. P. A. Benedetti, V. Evangelista, D. Guidarini, and S. Vestri, “Achieving confocal-point performance in confocal-line microscopy,” Bioimaging 2, 122–130 (1994).

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