Abstract

We present results of concurrent maximum-likelihood restoration implementations with a spatially variant point-spread function (SV-PSF) on both synthetic and real data sets from the Hubble Space Telescope. We demonstrate that SV-PSF restoration exhibits superior performance compared with restoration with a spatially invariant point-spread function. We realize concurrency on a network of Unix workstations and on a SV-PSF model from sparse point-spread function reference information by means of bilinear interpolation. We then use the interpolative point-spread function model to implement several different SV-PSF restoration methods. These restoration methods are tested on a standard synthetic Hubble Space Telescope test case, and the results are compared on a computational effort–restoration performance basis. These methods are further applied to actual Hubble Space Telescope data, including an application that corrects for motion blur, and the results are presented.

© 1996 Optical Society of America

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  3. C. J. Burrows, J. A. Holtzman, S. M. Faber, P. Y. Bely, H. Hasan, C. R. Lynds, D. Schroeder, “The imaging performance of the Hubble Space Telescope,” Astrophys. J. 369, L21–L26 (1991).
    [CrossRef]
  4. R. J. Hanisch, R. L. White, eds., The Restoration of HST Images and Spectra–II (Space Telescope Science Institute, Baltimore, Md., 1994).
  5. R. J. Hanisch, R. L. White, R. L. Gilliland, “Deconvolution of HST images and spectra,” in Deconvolution of Images and Spectra, P. A. Jansen, ed. (Academic, New York, to be published).
  6. M. L. Cobb, P. L. Hertz, R. O. Whaley, E. A. Hoffman, “Space variant point spread function deconvolution of Hubble imagery using the connection machine,” in Digital Image Recovery and Synthesis II, P. S. Idell, ed., Proc. SPIE2029, 202–207 (1993).
    [CrossRef]
  7. M. Faisal, A. D. Lanterman, D. L. Snyder, R. L. White, “Implementation of a modified Richardson–Lucy method for image restoration on a massively parallel computer to compensate for space-variant point spread of a charge-coupled-device camera,” J. Opt. Soc. Am. A 12, 2593–2603 (1995).
    [CrossRef]
  8. A. F. Boden, D. C. Redding, R. J. Hanisch, J. Mo, R. L. White, “Massively parallel spatially-invariant maximum likelihood image restoration,” Bull. Am. Astron. Soc. 27, 924–929 (1995).
  9. D. Redding, P. Dumont, J. Yu, “Hubble Space Telescope prescription retrieval,” Appl. Opt. 32, 1728–1736 (1993).
    [CrossRef] [PubMed]
  10. D. Redding, S. Sirlin, A. Boden, J. Mo, R. Hanisch, L. Furey, “The prescription of the HST,” in Calibrating Hubble Space Telescope: Post Servicing Mission, A. Koratkar, C. Leitherer, eds. (Space Telescope Science Institute, Baltimore, Md., 1995), p. 132.
  11. W. H. Richardson, “Bayesian-based iterative method of image restoration,”J. Opt. Soc. Am. 62, 55–59 (1972).
    [CrossRef]
  12. L. B. Lucy, “An iterative technique for the rectification of observed distributions,” Astron. J. 79, 745–754 (1974).
    [CrossRef]
  13. J. A. Högbom, “Aperture synthesis with a non-regular distribution of interferometer baselines,” Astron. Astrophys. Suppl. Ser. 15, 417–426 (1974).
  14. T. J. Cornwell, “A simple method of stabilizing the clean algorithm,” Astron. Astrophys. 121, 281–285 (1983).
  15. R. Narayan, R. Nityananda, “Maximum entropy image restoration in astronomy,” Annu. Rev. Astron. Astrophys. 24, 127–170 (1986).
    [CrossRef]
  16. I. C. Busko, “Evaluation of image restoration algorithms applied to HST images,” in The Restoration of HST Images and Spectra–II, R. J. Hanisch, R. L. White, eds. (Space Telescope Science Institute, Baltimore, Md., 1994), p. 279.
  17. H.-M. Adorf, “Towards HST restoration with a space-variant PSF, cosmic rays and other missing data,” in The Restoration of HST Images and Spectra–II, R. J. Hanisch, R. L. White, ed. (Space Telescope Science Institute, Baltimore, Md., 1994), p. 72.
  18. W. H. Press, B. P. Flannery, S. A. Teukolsky, W. T. Vetterling, Numerical Recipes: The Art of Scientific Computing (Cambridge U., Cambridge, UK, 1986).
  19. H. J. Trussel, B. R. Hunt, “Image restoration of space-variant blurs by sectioned methods,” in IEEE Trans. Acoust. Speech Signal Process. 26, 608–609 (1978).
    [CrossRef]
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  21. H. J. Trussel, B. R. Hunt, “Sectioned methods for image restoration,”IEEE Trans. Acoust. Speech Signal Process. 26, 157–164 (1978).
    [CrossRef]
  22. T. J. Holmes, Y.-H. Liu, “Acceleration of maximum-likelihood image restoration for fluorescence microscopy and other noncoherent imagery,” J. Opt. Soc. Am. A 8, 893–907 (1991).
    [CrossRef]
  23. R. N. Hook, L. B. Lucy, “Experiments with accelerated image restoration,” in Science with the Hubble Space Telescope, P. Benvenuti, E. Schreier, eds. (European Southern Observatory, Garching, Germany, 1992), p. 245.
  24. R. L. White, “Image restoration using the damped Richard-son–Lucy method,” in The Restoration of HST Images and Spectra–II, R. J. Hanisch, R. L. White, eds. (Space Telescope Science Institute, Baltimore, Md., 1994), p. 104.
  25. R. J. Hanisch, “WFPC simulation data sets available,” in Image Restoration Newsletter (Space Telescope Science Institute, Baltimore, Md., 1993), pp. 76–77.
  26. J. Krist, “HST PSF simulation using tiny tim,” in Proceedings of Astronomical Data Analysis Software and Systems II, ASP Conference Series 52 (Astronomical Society of the Pacific, San Francisco, Calif., 1993), p. 536.
  27. B. Reipurth, S. Heathcote, “The jet and energy source of HH 46/47,” Astron. Astrophys. 246, 511–534 (1991).
  28. S. Heathcote, J. A. Morse, P. Hartigan, B. Reipurth, J. Bally, R. D. Schwartz, J. M. Stone, “HST observations of the HH47 jet: narrow band images,” submitted to Astrophys. J.
  29. P. Madau, ed., Hubble Space Telescope Cycle 6 Call For Proposals (Space Telescope Science Institute, Baltimore, Md., 1995).
  30. J. Mo, R. J. Hanisch, “Restoration of HST WFPC2 images taken in gyro-hold mode,” in Proceedings of ADASS IV, ASP Conference Series 77 (Astronomical Society of the Pacific, San Francisco, Calif., 1995), p. 263.
  31. M. Shara, Space Telescope Science Institute, Baltimore, Md. 21218 (personal communication, 1994).
  32. N. Wu, “MEM task for image restoration in IRAF” in Proceedings of ADASS IV, ASP Conference Series 77 (Astronomical Society of the Pacific, San Francisco, Calif., 1995), p. 267.

1995

M. Faisal, A. D. Lanterman, D. L. Snyder, R. L. White, “Implementation of a modified Richardson–Lucy method for image restoration on a massively parallel computer to compensate for space-variant point spread of a charge-coupled-device camera,” J. Opt. Soc. Am. A 12, 2593–2603 (1995).
[CrossRef]

A. F. Boden, D. C. Redding, R. J. Hanisch, J. Mo, R. L. White, “Massively parallel spatially-invariant maximum likelihood image restoration,” Bull. Am. Astron. Soc. 27, 924–929 (1995).

1993

1991

B. Reipurth, S. Heathcote, “The jet and energy source of HH 46/47,” Astron. Astrophys. 246, 511–534 (1991).

T. J. Holmes, Y.-H. Liu, “Acceleration of maximum-likelihood image restoration for fluorescence microscopy and other noncoherent imagery,” J. Opt. Soc. Am. A 8, 893–907 (1991).
[CrossRef]

C. J. Burrows, J. A. Holtzman, S. M. Faber, P. Y. Bely, H. Hasan, C. R. Lynds, D. Schroeder, “The imaging performance of the Hubble Space Telescope,” Astrophys. J. 369, L21–L26 (1991).
[CrossRef]

1986

R. Narayan, R. Nityananda, “Maximum entropy image restoration in astronomy,” Annu. Rev. Astron. Astrophys. 24, 127–170 (1986).
[CrossRef]

1983

T. J. Cornwell, “A simple method of stabilizing the clean algorithm,” Astron. Astrophys. 121, 281–285 (1983).

1978

H. J. Trussel, B. R. Hunt, “Image restoration of space-variant blurs by sectioned methods,” in IEEE Trans. Acoust. Speech Signal Process. 26, 608–609 (1978).
[CrossRef]

H. J. Trussel, B. R. Hunt, “Sectioned methods for image restoration,”IEEE Trans. Acoust. Speech Signal Process. 26, 157–164 (1978).
[CrossRef]

1974

L. B. Lucy, “An iterative technique for the rectification of observed distributions,” Astron. J. 79, 745–754 (1974).
[CrossRef]

J. A. Högbom, “Aperture synthesis with a non-regular distribution of interferometer baselines,” Astron. Astrophys. Suppl. Ser. 15, 417–426 (1974).

1972

Adorf, H.-M.

H.-M. Adorf, “Towards HST restoration with a space-variant PSF, cosmic rays and other missing data,” in The Restoration of HST Images and Spectra–II, R. J. Hanisch, R. L. White, ed. (Space Telescope Science Institute, Baltimore, Md., 1994), p. 72.

Bally, J.

S. Heathcote, J. A. Morse, P. Hartigan, B. Reipurth, J. Bally, R. D. Schwartz, J. M. Stone, “HST observations of the HH47 jet: narrow band images,” submitted to Astrophys. J.

Bely, P. Y.

C. J. Burrows, J. A. Holtzman, S. M. Faber, P. Y. Bely, H. Hasan, C. R. Lynds, D. Schroeder, “The imaging performance of the Hubble Space Telescope,” Astrophys. J. 369, L21–L26 (1991).
[CrossRef]

Boden, A.

D. Redding, S. Sirlin, A. Boden, J. Mo, R. Hanisch, L. Furey, “The prescription of the HST,” in Calibrating Hubble Space Telescope: Post Servicing Mission, A. Koratkar, C. Leitherer, eds. (Space Telescope Science Institute, Baltimore, Md., 1995), p. 132.

Boden, A. F.

A. F. Boden, D. C. Redding, R. J. Hanisch, J. Mo, R. L. White, “Massively parallel spatially-invariant maximum likelihood image restoration,” Bull. Am. Astron. Soc. 27, 924–929 (1995).

Burrows, C. J.

C. J. Burrows, J. A. Holtzman, S. M. Faber, P. Y. Bely, H. Hasan, C. R. Lynds, D. Schroeder, “The imaging performance of the Hubble Space Telescope,” Astrophys. J. 369, L21–L26 (1991).
[CrossRef]

Busko, I. C.

I. C. Busko, “Evaluation of image restoration algorithms applied to HST images,” in The Restoration of HST Images and Spectra–II, R. J. Hanisch, R. L. White, eds. (Space Telescope Science Institute, Baltimore, Md., 1994), p. 279.

Cobb, M. L.

M. L. Cobb, P. L. Hertz, R. O. Whaley, E. A. Hoffman, “Space variant point spread function deconvolution of Hubble imagery using the connection machine,” in Digital Image Recovery and Synthesis II, P. S. Idell, ed., Proc. SPIE2029, 202–207 (1993).
[CrossRef]

Cornwell, T. J.

T. J. Cornwell, “A simple method of stabilizing the clean algorithm,” Astron. Astrophys. 121, 281–285 (1983).

Dumont, P.

Faber, S. M.

C. J. Burrows, J. A. Holtzman, S. M. Faber, P. Y. Bely, H. Hasan, C. R. Lynds, D. Schroeder, “The imaging performance of the Hubble Space Telescope,” Astrophys. J. 369, L21–L26 (1991).
[CrossRef]

Faisal, M.

M. Faisal, A. D. Lanterman, D. L. Snyder, R. L. White, “Implementation of a modified Richardson–Lucy method for image restoration on a massively parallel computer to compensate for space-variant point spread of a charge-coupled-device camera,” J. Opt. Soc. Am. A 12, 2593–2603 (1995).
[CrossRef]

Flannery, B. P.

W. H. Press, B. P. Flannery, S. A. Teukolsky, W. T. Vetterling, Numerical Recipes: The Art of Scientific Computing (Cambridge U., Cambridge, UK, 1986).

Furey, L.

D. Redding, S. Sirlin, A. Boden, J. Mo, R. Hanisch, L. Furey, “The prescription of the HST,” in Calibrating Hubble Space Telescope: Post Servicing Mission, A. Koratkar, C. Leitherer, eds. (Space Telescope Science Institute, Baltimore, Md., 1995), p. 132.

Gilliland, R. L.

R. J. Hanisch, R. L. White, R. L. Gilliland, “Deconvolution of HST images and spectra,” in Deconvolution of Images and Spectra, P. A. Jansen, ed. (Academic, New York, to be published).

Hanisch, R.

D. Redding, S. Sirlin, A. Boden, J. Mo, R. Hanisch, L. Furey, “The prescription of the HST,” in Calibrating Hubble Space Telescope: Post Servicing Mission, A. Koratkar, C. Leitherer, eds. (Space Telescope Science Institute, Baltimore, Md., 1995), p. 132.

Hanisch, R. J.

A. F. Boden, D. C. Redding, R. J. Hanisch, J. Mo, R. L. White, “Massively parallel spatially-invariant maximum likelihood image restoration,” Bull. Am. Astron. Soc. 27, 924–929 (1995).

R. J. Hanisch, “WFPC simulation data sets available,” in Image Restoration Newsletter (Space Telescope Science Institute, Baltimore, Md., 1993), pp. 76–77.

J. Mo, R. J. Hanisch, “Restoration of HST WFPC2 images taken in gyro-hold mode,” in Proceedings of ADASS IV, ASP Conference Series 77 (Astronomical Society of the Pacific, San Francisco, Calif., 1995), p. 263.

R. J. Hanisch, R. L. White, R. L. Gilliland, “Deconvolution of HST images and spectra,” in Deconvolution of Images and Spectra, P. A. Jansen, ed. (Academic, New York, to be published).

Hartigan, P.

S. Heathcote, J. A. Morse, P. Hartigan, B. Reipurth, J. Bally, R. D. Schwartz, J. M. Stone, “HST observations of the HH47 jet: narrow band images,” submitted to Astrophys. J.

Hasan, H.

C. J. Burrows, J. A. Holtzman, S. M. Faber, P. Y. Bely, H. Hasan, C. R. Lynds, D. Schroeder, “The imaging performance of the Hubble Space Telescope,” Astrophys. J. 369, L21–L26 (1991).
[CrossRef]

Heathcote, S.

B. Reipurth, S. Heathcote, “The jet and energy source of HH 46/47,” Astron. Astrophys. 246, 511–534 (1991).

S. Heathcote, J. A. Morse, P. Hartigan, B. Reipurth, J. Bally, R. D. Schwartz, J. M. Stone, “HST observations of the HH47 jet: narrow band images,” submitted to Astrophys. J.

Hertz, P. L.

M. L. Cobb, P. L. Hertz, R. O. Whaley, E. A. Hoffman, “Space variant point spread function deconvolution of Hubble imagery using the connection machine,” in Digital Image Recovery and Synthesis II, P. S. Idell, ed., Proc. SPIE2029, 202–207 (1993).
[CrossRef]

Hoffman, E. A.

M. L. Cobb, P. L. Hertz, R. O. Whaley, E. A. Hoffman, “Space variant point spread function deconvolution of Hubble imagery using the connection machine,” in Digital Image Recovery and Synthesis II, P. S. Idell, ed., Proc. SPIE2029, 202–207 (1993).
[CrossRef]

Högbom, J. A.

J. A. Högbom, “Aperture synthesis with a non-regular distribution of interferometer baselines,” Astron. Astrophys. Suppl. Ser. 15, 417–426 (1974).

Holmes, T. J.

Holtzman, J. A.

C. J. Burrows, J. A. Holtzman, S. M. Faber, P. Y. Bely, H. Hasan, C. R. Lynds, D. Schroeder, “The imaging performance of the Hubble Space Telescope,” Astrophys. J. 369, L21–L26 (1991).
[CrossRef]

Hook, R. N.

R. N. Hook, L. B. Lucy, “Experiments with accelerated image restoration,” in Science with the Hubble Space Telescope, P. Benvenuti, E. Schreier, eds. (European Southern Observatory, Garching, Germany, 1992), p. 245.

Hunt, B. R.

H. J. Trussel, B. R. Hunt, “Sectioned methods for image restoration,”IEEE Trans. Acoust. Speech Signal Process. 26, 157–164 (1978).
[CrossRef]

H. J. Trussel, B. R. Hunt, “Image restoration of space-variant blurs by sectioned methods,” in IEEE Trans. Acoust. Speech Signal Process. 26, 608–609 (1978).
[CrossRef]

Krist, J.

J. Krist, “HST PSF simulation using tiny tim,” in Proceedings of Astronomical Data Analysis Software and Systems II, ASP Conference Series 52 (Astronomical Society of the Pacific, San Francisco, Calif., 1993), p. 536.

Lanterman, A. D.

M. Faisal, A. D. Lanterman, D. L. Snyder, R. L. White, “Implementation of a modified Richardson–Lucy method for image restoration on a massively parallel computer to compensate for space-variant point spread of a charge-coupled-device camera,” J. Opt. Soc. Am. A 12, 2593–2603 (1995).
[CrossRef]

Liu, Y.-H.

Lucy, L. B.

L. B. Lucy, “An iterative technique for the rectification of observed distributions,” Astron. J. 79, 745–754 (1974).
[CrossRef]

R. N. Hook, L. B. Lucy, “Experiments with accelerated image restoration,” in Science with the Hubble Space Telescope, P. Benvenuti, E. Schreier, eds. (European Southern Observatory, Garching, Germany, 1992), p. 245.

Lynds, C. R.

C. J. Burrows, J. A. Holtzman, S. M. Faber, P. Y. Bely, H. Hasan, C. R. Lynds, D. Schroeder, “The imaging performance of the Hubble Space Telescope,” Astrophys. J. 369, L21–L26 (1991).
[CrossRef]

Mo, J.

A. F. Boden, D. C. Redding, R. J. Hanisch, J. Mo, R. L. White, “Massively parallel spatially-invariant maximum likelihood image restoration,” Bull. Am. Astron. Soc. 27, 924–929 (1995).

D. Redding, S. Sirlin, A. Boden, J. Mo, R. Hanisch, L. Furey, “The prescription of the HST,” in Calibrating Hubble Space Telescope: Post Servicing Mission, A. Koratkar, C. Leitherer, eds. (Space Telescope Science Institute, Baltimore, Md., 1995), p. 132.

J. Mo, R. J. Hanisch, “Restoration of HST WFPC2 images taken in gyro-hold mode,” in Proceedings of ADASS IV, ASP Conference Series 77 (Astronomical Society of the Pacific, San Francisco, Calif., 1995), p. 263.

Morse, J. A.

S. Heathcote, J. A. Morse, P. Hartigan, B. Reipurth, J. Bally, R. D. Schwartz, J. M. Stone, “HST observations of the HH47 jet: narrow band images,” submitted to Astrophys. J.

Narayan, R.

R. Narayan, R. Nityananda, “Maximum entropy image restoration in astronomy,” Annu. Rev. Astron. Astrophys. 24, 127–170 (1986).
[CrossRef]

Nityananda, R.

R. Narayan, R. Nityananda, “Maximum entropy image restoration in astronomy,” Annu. Rev. Astron. Astrophys. 24, 127–170 (1986).
[CrossRef]

Press, W. H.

W. H. Press, B. P. Flannery, S. A. Teukolsky, W. T. Vetterling, Numerical Recipes: The Art of Scientific Computing (Cambridge U., Cambridge, UK, 1986).

Redding, D.

D. Redding, P. Dumont, J. Yu, “Hubble Space Telescope prescription retrieval,” Appl. Opt. 32, 1728–1736 (1993).
[CrossRef] [PubMed]

D. Redding, S. Sirlin, A. Boden, J. Mo, R. Hanisch, L. Furey, “The prescription of the HST,” in Calibrating Hubble Space Telescope: Post Servicing Mission, A. Koratkar, C. Leitherer, eds. (Space Telescope Science Institute, Baltimore, Md., 1995), p. 132.

Redding, D. C.

A. F. Boden, D. C. Redding, R. J. Hanisch, J. Mo, R. L. White, “Massively parallel spatially-invariant maximum likelihood image restoration,” Bull. Am. Astron. Soc. 27, 924–929 (1995).

Reipurth, B.

B. Reipurth, S. Heathcote, “The jet and energy source of HH 46/47,” Astron. Astrophys. 246, 511–534 (1991).

S. Heathcote, J. A. Morse, P. Hartigan, B. Reipurth, J. Bally, R. D. Schwartz, J. M. Stone, “HST observations of the HH47 jet: narrow band images,” submitted to Astrophys. J.

Richardson, W. H.

Schroeder, D.

C. J. Burrows, J. A. Holtzman, S. M. Faber, P. Y. Bely, H. Hasan, C. R. Lynds, D. Schroeder, “The imaging performance of the Hubble Space Telescope,” Astrophys. J. 369, L21–L26 (1991).
[CrossRef]

Schwartz, R. D.

S. Heathcote, J. A. Morse, P. Hartigan, B. Reipurth, J. Bally, R. D. Schwartz, J. M. Stone, “HST observations of the HH47 jet: narrow band images,” submitted to Astrophys. J.

Shara, M.

M. Shara, Space Telescope Science Institute, Baltimore, Md. 21218 (personal communication, 1994).

Sirlin, S.

D. Redding, S. Sirlin, A. Boden, J. Mo, R. Hanisch, L. Furey, “The prescription of the HST,” in Calibrating Hubble Space Telescope: Post Servicing Mission, A. Koratkar, C. Leitherer, eds. (Space Telescope Science Institute, Baltimore, Md., 1995), p. 132.

Snyder, D. L.

M. Faisal, A. D. Lanterman, D. L. Snyder, R. L. White, “Implementation of a modified Richardson–Lucy method for image restoration on a massively parallel computer to compensate for space-variant point spread of a charge-coupled-device camera,” J. Opt. Soc. Am. A 12, 2593–2603 (1995).
[CrossRef]

Stone, J. M.

S. Heathcote, J. A. Morse, P. Hartigan, B. Reipurth, J. Bally, R. D. Schwartz, J. M. Stone, “HST observations of the HH47 jet: narrow band images,” submitted to Astrophys. J.

Teukolsky, S. A.

W. H. Press, B. P. Flannery, S. A. Teukolsky, W. T. Vetterling, Numerical Recipes: The Art of Scientific Computing (Cambridge U., Cambridge, UK, 1986).

Trussel, H. J.

H. J. Trussel, B. R. Hunt, “Image restoration of space-variant blurs by sectioned methods,” in IEEE Trans. Acoust. Speech Signal Process. 26, 608–609 (1978).
[CrossRef]

H. J. Trussel, B. R. Hunt, “Sectioned methods for image restoration,”IEEE Trans. Acoust. Speech Signal Process. 26, 157–164 (1978).
[CrossRef]

Vetterling, W. T.

W. H. Press, B. P. Flannery, S. A. Teukolsky, W. T. Vetterling, Numerical Recipes: The Art of Scientific Computing (Cambridge U., Cambridge, UK, 1986).

Whaley, R. O.

M. L. Cobb, P. L. Hertz, R. O. Whaley, E. A. Hoffman, “Space variant point spread function deconvolution of Hubble imagery using the connection machine,” in Digital Image Recovery and Synthesis II, P. S. Idell, ed., Proc. SPIE2029, 202–207 (1993).
[CrossRef]

White, R. L.

A. F. Boden, D. C. Redding, R. J. Hanisch, J. Mo, R. L. White, “Massively parallel spatially-invariant maximum likelihood image restoration,” Bull. Am. Astron. Soc. 27, 924–929 (1995).

M. Faisal, A. D. Lanterman, D. L. Snyder, R. L. White, “Implementation of a modified Richardson–Lucy method for image restoration on a massively parallel computer to compensate for space-variant point spread of a charge-coupled-device camera,” J. Opt. Soc. Am. A 12, 2593–2603 (1995).
[CrossRef]

R. L. White, “Image restoration using the damped Richard-son–Lucy method,” in The Restoration of HST Images and Spectra–II, R. J. Hanisch, R. L. White, eds. (Space Telescope Science Institute, Baltimore, Md., 1994), p. 104.

R. J. Hanisch, R. L. White, R. L. Gilliland, “Deconvolution of HST images and spectra,” in Deconvolution of Images and Spectra, P. A. Jansen, ed. (Academic, New York, to be published).

Wu, N.

N. Wu, “MEM task for image restoration in IRAF” in Proceedings of ADASS IV, ASP Conference Series 77 (Astronomical Society of the Pacific, San Francisco, Calif., 1995), p. 267.

Yu, J.

Annu. Rev. Astron. Astrophys.

R. Narayan, R. Nityananda, “Maximum entropy image restoration in astronomy,” Annu. Rev. Astron. Astrophys. 24, 127–170 (1986).
[CrossRef]

Appl. Opt.

Astron. Astrophys.

T. J. Cornwell, “A simple method of stabilizing the clean algorithm,” Astron. Astrophys. 121, 281–285 (1983).

Astron. Astrophys.

B. Reipurth, S. Heathcote, “The jet and energy source of HH 46/47,” Astron. Astrophys. 246, 511–534 (1991).

Astron. Astrophys. Suppl. Ser.

J. A. Högbom, “Aperture synthesis with a non-regular distribution of interferometer baselines,” Astron. Astrophys. Suppl. Ser. 15, 417–426 (1974).

Astron. J.

L. B. Lucy, “An iterative technique for the rectification of observed distributions,” Astron. J. 79, 745–754 (1974).
[CrossRef]

Astrophys. J.

C. J. Burrows, J. A. Holtzman, S. M. Faber, P. Y. Bely, H. Hasan, C. R. Lynds, D. Schroeder, “The imaging performance of the Hubble Space Telescope,” Astrophys. J. 369, L21–L26 (1991).
[CrossRef]

Bull. Am. Astron. Soc.

A. F. Boden, D. C. Redding, R. J. Hanisch, J. Mo, R. L. White, “Massively parallel spatially-invariant maximum likelihood image restoration,” Bull. Am. Astron. Soc. 27, 924–929 (1995).

IEEE Trans. Acoust. Speech Signal Process.

H. J. Trussel, B. R. Hunt, “Image restoration of space-variant blurs by sectioned methods,” in IEEE Trans. Acoust. Speech Signal Process. 26, 608–609 (1978).
[CrossRef]

IEEE Trans. Acoust. Speech Signal Process.

H. J. Trussel, B. R. Hunt, “Sectioned methods for image restoration,”IEEE Trans. Acoust. Speech Signal Process. 26, 157–164 (1978).
[CrossRef]

J. Opt. Soc. Am. A

M. Faisal, A. D. Lanterman, D. L. Snyder, R. L. White, “Implementation of a modified Richardson–Lucy method for image restoration on a massively parallel computer to compensate for space-variant point spread of a charge-coupled-device camera,” J. Opt. Soc. Am. A 12, 2593–2603 (1995).
[CrossRef]

J. Opt. Soc. Am.

J. Opt. Soc. Am. A

Other

R. N. Hook, L. B. Lucy, “Experiments with accelerated image restoration,” in Science with the Hubble Space Telescope, P. Benvenuti, E. Schreier, eds. (European Southern Observatory, Garching, Germany, 1992), p. 245.

R. L. White, “Image restoration using the damped Richard-son–Lucy method,” in The Restoration of HST Images and Spectra–II, R. J. Hanisch, R. L. White, eds. (Space Telescope Science Institute, Baltimore, Md., 1994), p. 104.

R. J. Hanisch, “WFPC simulation data sets available,” in Image Restoration Newsletter (Space Telescope Science Institute, Baltimore, Md., 1993), pp. 76–77.

J. Krist, “HST PSF simulation using tiny tim,” in Proceedings of Astronomical Data Analysis Software and Systems II, ASP Conference Series 52 (Astronomical Society of the Pacific, San Francisco, Calif., 1993), p. 536.

S. Heathcote, J. A. Morse, P. Hartigan, B. Reipurth, J. Bally, R. D. Schwartz, J. M. Stone, “HST observations of the HH47 jet: narrow band images,” submitted to Astrophys. J.

P. Madau, ed., Hubble Space Telescope Cycle 6 Call For Proposals (Space Telescope Science Institute, Baltimore, Md., 1995).

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Figures (4)

Fig. 1
Fig. 1

(a) WF/PC-1 and (b) WFPC2 star cluster test case SNR performance. mprl restoration performance on the star cluster test case is given for both (a) and (b), in both square and absolute deviation SNR’s. In all the cases shown, deconvolutions with the SV-PSF model outperform deconvolutions with a single PSF corresponding to the center of the subfield. For moderate (less than ≈1000) iteration counts the nominal R-L algorithm outperforms the damped R-L algorithm.24 However, at higher numbers of iterations the damped algorithm performance exceeds that of the nominal R-L when judged by the absolute deviation metric (which correlates better with visual quality).

Fig. 2
Fig. 2

Narrow-band WFPC2 observations of the HH 46/47 complex. (a) Average of four raw exposures of the HH 46/47 complex obtained by Heathcote et al.28 (principal investigator, Reipurth) in S ii, using WFPC2 WF3. (b) SV-PSF mprl-restored version, superimposed on a smooth model of the background. Stars (with the exception of the saturated star, lower left) are seen to restore to tight point sources over the full field of a WF chip (approximately 1.33 × 1.33 arcmin), and contrast and resolution of the jet structure morphology is enhanced in the restored version. This restoration was used in the NASA press release and in scientific publication of these data.

Fig. 3
Fig. 3

Contour plots of S ii HH 46/47 imagery before and after restoration. (a) Contour plot of the bow shock emission region HH 47a (Ref. 27) in the WFPC2 WF S ii imagery of Ref. 28 (size is 15 × 15 arcsec). (b) Same region after SV-PSF restoration with mprl (Fig. 2). (c) HH 46 and reflection nebula region from the WFPC2 WF S ii imagery of Ref. 28 (size is 30 × 30 arcsec). (d) HH 46 region from the same mprl restoration. The dynamic range and the spatial resolution are considerably higher in the restored versions. This restoration was used in the NASA press release and in scientific publication of these data.

Fig. 4
Fig. 4

HST motion blur compensation. Upper left: extracted from the original WFPC2 WF2 snapshot image of NGC 422,31 blurring of point sources from HST motion of HST during the exposure is evident. Upper right: provisional (R-L) deconvolu0tion with a tiny tim PSF. Line sources indicate HST pointing motion. Several of the brightest lines are averaged together to construct an empirical motion blur kernel, and a resulting effective PSF model. Lower left: deconvolution of original data with effective PSF model by maximum-entropy method.32 Lower right: deconvolution of original data with effective PSF model by R-L method. The effects of HST pointing motion are mitigated; point sources are consistently restored to tight concentrations, and the results are insensitive to the deconvolution method.30

Tables (2)

Tables Icon

Table 1 Comparative Restoration Performance, WF/PC-1 Star Cluster Test Casea

Tables Icon

Table 2 Comparative Restoration Performance, Single-grid versus Double-grid SV-PSF Methodsa

Equations (5)

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I ( x ) = O ( x ) P ( x , x ) d x .
I q ( x q ) = x q O q ( x q ) P q ( x q , x q ) ,
P q ( x q , x q ) = P q ( x q - x q ) .
SNR 2 20 log [ i truth i i ( truth i - estimate i ) 2 ] , SNR 1 20 log [ i truth i i truth i - estimate i ] ,
P ¯ N 1 - i N truth i - estimate i truth i N ,

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