Skip to main content
SpringerLink
Log in

Deconvolution in Optical Astronomy. A Bayesian Approach

  • Conference paper
Stochastic Models, Statistical Methods, and Algorithms in Image Analysis

Part of the book series: Lecture Notes in Statistics ((LNS,volume 74))

Abstract

We describe in this work how the Bayesian paradigm can be applied to a deconvolution problem in optical astronomy. The use of robust statistics in this process is also discussed.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Buonanno, R., Buscema, G., Corsi, C.E.; Ferraro, I. and Iannicola, G. 1983. Automated photographic photometry of stars in globular clusters. Astron. Astrophys., 126, 126–278.

    Google Scholar 

  2. Hampel, F.R., Ronchetti, E.M., Rousseeuw, P.J. and Stahel, W.A. 1986. Robust Statistics: The Approach Based on Influence Functions. Wiley.

    Google Scholar 

  3. Huber, P.J. 1981. Robust Statistics. Wiley.

    Google Scholar 

  4. Moffat, A.F.J. 1969. A theoretical investigation of focal stellar images in the photographic emulsion and application to photographic photometry. Astrom. Astrophys., 3, 455–462.

    Google Scholar 

  5. Molina, R., Pérez de la Blanca, N. and Ripley, B.D. 1989. Statistical restoration of astronomical images. In Di Gesu, V.D., Scarsi, L., Crane, P. and Friedman, J.H. Eds. Data Analysis in Astronomy III, Plenum Publishing Corporation,. 75–82.

    Google Scholar 

  6. Molina, R. and Ripley, B.D. 1989. Using spatial models as priors in image analysis. J. Appl. Statist, 16, 193–206.

    Article  Google Scholar 

  7. Molina, R., del Olmo, A., Perea, J. and Ripley, B.D. 1990. Bayesian deconvolution in optical astronomy. Submitted to Astrom. J.

    Google Scholar 

  8. Ripley, B.D. 1981. Spatial Statistics. Wiley.

    Book  MATH  Google Scholar 

  9. Ripley, B.D. 1988. Statistical Inference for Spatial Processes .Cambridge University Press.

    Google Scholar 

  10. Singleton, R.C. 1969. An algorithm for computing the mixed radii fast Fourier. IEEE Transactions on Audio and Electroacoustics, AU-17. 93–103

    Google Scholar 

  11. Takase, B., Kodaira, K. and Okamura, S. 1984. An Atlas of Selected Galaxies.University of Tokyo Press.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Departamento de Ciencias de la Computación e I.A., Universidad de Granada, 18071, Granada, España, Spain

    R. Molina

  2. Department of Statistics, University of Oxford, Oxford, OX1 3TG, UK

    B. D. Ripley

Authors
  1. R. Molina
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. B. D. Ripley
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Istituto per le Applicazioni del Calcolo, C.N.R., Viale del Policlinico 137, 00161, Rome, Italy

    Piero Barone  & Arnoldo Frigessi  & 

  2. Dipartimento di Matematica Pura ed Applicata, Università di L’Aquila, L’Aquila, Italy

    Mauro Piccioni

Rights and permissions

Reprints and permissions

Copyright information

© 1992 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Molina, R., Ripley, B.D. (1992). Deconvolution in Optical Astronomy. A Bayesian Approach. In: Barone, P., Frigessi, A., Piccioni, M. (eds) Stochastic Models, Statistical Methods, and Algorithms in Image Analysis. Lecture Notes in Statistics, vol 74. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-2920-9_16

Download citation

  • DOI: https://doi.org/10.1007/978-1-4612-2920-9_16

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-0-387-97810-9

  • Online ISBN: 978-1-4612-2920-9

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics

Search

Navigation