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Optics Express

Optics Express

  • Editor: J. H. Eberly
  • Vol. 1, Iss. 11 — Nov. 24, 1997
  • pp: 347–354

Reduction of nonstationary noise in telescope imagery using a support constraint

D.W. Tyler and C.L. Matson  »View Author Affiliations


Optics Express, Vol. 1, Issue 11, pp. 347-354 (1997)
http://dx.doi.org/10.1364/OE.1.000347


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Abstract

We demonstrate the use of image support constraints in a noise-reduction algorithm. Previous work has revealed serious limits to the use of support if image noise is wide-sense stationary in the frequency domain; we use simulation and numerical calculations to show these limits are removed for nonstationary noise generated by inverse-filtering adaptive optics image spectra. To quantify the noise reduction, we plot fractional noise removed by the proposed algorithm over a range of support sizes. We repeat this calculation for other noise sources with varying degrees of stationarity.

© Optical Society of America

OCIS Codes
(100.1830) Image processing : Deconvolution
(100.2000) Image processing : Digital image processing
(100.2980) Image processing : Image enhancement
(100.3010) Image processing : Image reconstruction techniques
(100.3190) Image processing : Inverse problems
(110.4280) Imaging systems : Noise in imaging systems

ToC Category:
Focus Issue: Signal collection and recovery

History
Original Manuscript: September 10, 1997
Published: November 24, 1997

Citation
David Tyler and Charles Matson, "Reduction of nonstationary noise in telescope imagery using a support constraint," Opt. Express 1, 347-354 (1997)
http://www.opticsinfobase.org/oe/abstract.cfm?URI=oe-1-11-347


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References

  1. C.K. Rushforth, "Signal restoration, functional analysis, and Fredholm integral equations of the first kind," in Image Recovery: Theory and Application, H. Stark, ed. (Academic Press, San Diego, CA, 1987), p. 46
  2. C.L. Matson, "Variance reduction in Fourier spectra and their corresponding images with the use of support constraints," J. Opt. Soc. Am. A 11, p. 97 (1994) [CrossRef]
  3. A. Papoulis, "Spectral reprentation of random signals," in Probability, Random Variables, and Stochastic Processes, (McGraw-Hill, New York 1991), p. 418
  4. M.C. Roggemann, E.L. Caudill, D.W. Tyler, M.J. Fox, M.A. Von Bokern, and C.L. Matson, "Compensated speckle imaging: Theory and experimental results," Appl. Opt. 33, 3099 (1994) [CrossRef] [PubMed]
  5. M.C. Roggemann, D.W. Tyler, and M.F. Bilmont, "Linear reconstruction of compensated images: theory and experimental results," Appl. Opt. 31, 7429 (1992) [CrossRef] [PubMed]
  6. C.L. Matson and M.C. Roggemann, "Noise reduction in adaptive optics imagery with the use of support constraints," Appl. Opt. 34, 767 (1995) [CrossRef] [PubMed]
  7. C.L. Matson, "Fourier spectrum extrapolation and enhancement using support constraints," IEEE Trans. Signal Process. 42, 156 (1994) [CrossRef]

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