L. Gilles, C. R. Vogel, and J. M. Bardsley, “Computational Methods for a Large-Scale Inverse Problem Arising in Atmospheric Optics,” Inverse Probl. 18, 237–252 (2002).
[Crossref]
J. G. Nagy and D. P. O’Leary, “Restoring images degraded by spatially-variant blur,” SIAM J. Sci. Comput. 19, 1063–1082 (1998).
[Crossref]
A. F. Boden, D. C. Redding, R. J. Hanisch, and J. Mo, “Massively Parallel Spatially-Variant Maximum Likelihood Restoration of Hubble Space Telescope Imagery,” J. Opt. Soc. Am. A 13, 1537–1545 (1996).
[Crossref]
D. A. Fish, J. Grochmalicki, and E. R. Pike, “Scanning singular-value-decomposition method for restoration of images with space-variant blur,” J. Opt. Soc. Am. A 13, 1–6 (1996).
[Crossref]
R. G. Paxman, B. J. Thelen, and J. H. Seldin, “Phase-diversity correction of turbulence-induced space-variant blur,” Opt. Lett. 19(16), 1231–1233 (1994).
[Crossref]
[PubMed]
H.-M. Adorf, “Towards HST restoration with space-variant PSF, cosmic rays and other missing data,” in The Restoration of HST Images and Spectra II, R. J. Hanisch and R. L. White, eds., pp. 72–78 (1994).
R. A. Gonsalves, “Phase diversity in adaptive optics,” Opt. Eng. 21, 829–832 (1982).
H. J. Trussell and B. R. Hunt, “Image Restoration of Space-Variant Blurs by Sectional Methods,” IEEE Trans. Acoust. Speech, Signal Processing 26, 608–609 (1978).
[Crossref]
H.-M. Adorf, “Towards HST restoration with space-variant PSF, cosmic rays and other missing data,” in The Restoration of HST Images and Spectra II, R. J. Hanisch and R. L. White, eds., pp. 72–78 (1994).
L. Gilles, C. R. Vogel, and J. M. Bardsley, “Computational Methods for a Large-Scale Inverse Problem Arising in Atmospheric Optics,” Inverse Probl. 18, 237–252 (2002).
[Crossref]
J. Biretta, “WFPC and WFPC 2 instrumental characteristics,” in The Restoration of HST Images and Spectra II, R. J. Hanisch and R. L. White, eds., pp. 224–235 (Space Telescope Science Institute, Baltimore, MD, 1994).
C. R. Vogel, T. Chan, and R. J. Plemmons, “Fast algorithms for phase diversity-based blind deconvolution,” in Adaptive Optical System Technologies, vol. 3353 (SPIE, 1998).
H. W. Engl, M. Hanke, and A. Neubauer, Regularization of Inverse Problems (Kluwer Academic Publishers, Dordrecht, 2000).
D. A. Fish, J. Grochmalicki, and E. R. Pike, “Scanning singular-value-decomposition method for restoration of images with space-variant blur,” J. Opt. Soc. Am. A 13, 1–6 (1996).
[Crossref]
H. J. Trussell and S. Fogel, “Identification and restoration of spatially variant motion blurs in sequential images,” IEEE Trans. Image Proc. 1, 123–126 (1992).
[Crossref]
L. Gilles, C. R. Vogel, and J. M. Bardsley, “Computational Methods for a Large-Scale Inverse Problem Arising in Atmospheric Optics,” Inverse Probl. 18, 237–252 (2002).
[Crossref]
R. A. Gonsalves, “Phase diversity in adaptive optics,” Opt. Eng. 21, 829–832 (1982).
D. A. Fish, J. Grochmalicki, and E. R. Pike, “Scanning singular-value-decomposition method for restoration of images with space-variant blur,” J. Opt. Soc. Am. A 13, 1–6 (1996).
[Crossref]
H. W. Engl, M. Hanke, and A. Neubauer, Regularization of Inverse Problems (Kluwer Academic Publishers, Dordrecht, 2000).
P. C. Hansen, Rank-deficient and discrete ill-posed problems (SIAM, Philadelphia, PA, 1997).
H. J. Trussell and B. R. Hunt, “Image Restoration of Space-Variant Blurs by Sectional Methods,” IEEE Trans. Acoust. Speech, Signal Processing 26, 608–609 (1978).
[Crossref]
J. G. Nagy and D. P. O’Leary, “Restoring images degraded by spatially-variant blur,” SIAM J. Sci. Comput. 19, 1063–1082 (1998).
[Crossref]
J. G. Nagy and D. P. O’Leary, “Fast iterative image restoration with a spatially varying PSF,” in Advanced Signal Processing Algorithms, Architectures, and Implementations VII, F. T. Luk, ed., vol. 3162, pp. 388–399 (SPIE, 1997).
H. W. Engl, M. Hanke, and A. Neubauer, Regularization of Inverse Problems (Kluwer Academic Publishers, Dordrecht, 2000).
J. Nocedal and S. J. Wright, Numerical Optimization (Springer-Verlag, New York, 1999).
[Crossref]
J. G. Nagy and D. P. O’Leary, “Restoring images degraded by spatially-variant blur,” SIAM J. Sci. Comput. 19, 1063–1082 (1998).
[Crossref]
J. G. Nagy and D. P. O’Leary, “Fast iterative image restoration with a spatially varying PSF,” in Advanced Signal Processing Algorithms, Architectures, and Implementations VII, F. T. Luk, ed., vol. 3162, pp. 388–399 (SPIE, 1997).
R. G. Paxman, B. J. Thelen, and J. H. Seldin, “Phase-diversity correction of turbulence-induced space-variant blur,” Opt. Lett. 19(16), 1231–1233 (1994).
[Crossref]
[PubMed]
R. G. Paxman, T. Schulz, and J. Fienup, “Joint estimation of object and aberrations by using phase diversity,” J. Opt. Soc. Am. A 9, 1072–1085 (1992).
[Crossref]
D. A. Fish, J. Grochmalicki, and E. R. Pike, “Scanning singular-value-decomposition method for restoration of images with space-variant blur,” J. Opt. Soc. Am. A 13, 1–6 (1996).
[Crossref]
C. R. Vogel, T. Chan, and R. J. Plemmons, “Fast algorithms for phase diversity-based blind deconvolution,” in Adaptive Optical System Technologies, vol. 3353 (SPIE, 1998).
M. C. Roggemann and B. Welsh, Imaging Through Turbulence (CRC Press, Boca Raton, FL, 1996).
H. J. Trussell and S. Fogel, “Identification and restoration of spatially variant motion blurs in sequential images,” IEEE Trans. Image Proc. 1, 123–126 (1992).
[Crossref]
H. J. Trussell and B. R. Hunt, “Image Restoration of Space-Variant Blurs by Sectional Methods,” IEEE Trans. Acoust. Speech, Signal Processing 26, 608–609 (1978).
[Crossref]
L. Gilles, C. R. Vogel, and J. M. Bardsley, “Computational Methods for a Large-Scale Inverse Problem Arising in Atmospheric Optics,” Inverse Probl. 18, 237–252 (2002).
[Crossref]
C. R. Vogel, T. Chan, and R. J. Plemmons, “Fast algorithms for phase diversity-based blind deconvolution,” in Adaptive Optical System Technologies, vol. 3353 (SPIE, 1998).
C. R. Vogel, Computational Methods for Inverse Problems (SIAM, Philadelphia, PA, 2002).
[Crossref]
M. C. Roggemann and B. Welsh, Imaging Through Turbulence (CRC Press, Boca Raton, FL, 1996).
J. Nocedal and S. J. Wright, Numerical Optimization (Springer-Verlag, New York, 1999).
[Crossref]
H. J. Trussell and B. R. Hunt, “Image Restoration of Space-Variant Blurs by Sectional Methods,” IEEE Trans. Acoust. Speech, Signal Processing 26, 608–609 (1978).
[Crossref]
H. J. Trussell and S. Fogel, “Identification and restoration of spatially variant motion blurs in sequential images,” IEEE Trans. Image Proc. 1, 123–126 (1992).
[Crossref]
L. Gilles, C. R. Vogel, and J. M. Bardsley, “Computational Methods for a Large-Scale Inverse Problem Arising in Atmospheric Optics,” Inverse Probl. 18, 237–252 (2002).
[Crossref]
D. A. Fish, J. Grochmalicki, and E. R. Pike, “Scanning singular-value-decomposition method for restoration of images with space-variant blur,” J. Opt. Soc. Am. A 13, 1–6 (1996).
[Crossref]
M. Faisal, A. D. Lanterman, D. L. Snyder, and 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 Function 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, and J. Mo, “Massively Parallel Spatially-Variant Maximum Likelihood Restoration of Hubble Space Telescope Imagery,” J. Opt. Soc. Am. A 13, 1537–1545 (1996).
[Crossref]
R. G. Paxman, T. Schulz, and J. Fienup, “Joint estimation of object and aberrations by using phase diversity,” J. Opt. Soc. Am. A 9, 1072–1085 (1992).
[Crossref]
R. A. Gonsalves, “Phase diversity in adaptive optics,” Opt. Eng. 21, 829–832 (1982).
J. G. Nagy and D. P. O’Leary, “Restoring images degraded by spatially-variant blur,” SIAM J. Sci. Comput. 19, 1063–1082 (1998).
[Crossref]
M. C. Roggemann and B. Welsh, Imaging Through Turbulence (CRC Press, Boca Raton, FL, 1996).
C. R. Vogel, T. Chan, and R. J. Plemmons, “Fast algorithms for phase diversity-based blind deconvolution,” in Adaptive Optical System Technologies, vol. 3353 (SPIE, 1998).
J. Biretta, “WFPC and WFPC 2 instrumental characteristics,” in The Restoration of HST Images and Spectra II, R. J. Hanisch and R. L. White, eds., pp. 224–235 (Space Telescope Science Institute, Baltimore, MD, 1994).
J. Nocedal and S. J. Wright, Numerical Optimization (Springer-Verlag, New York, 1999).
[Crossref]
H.-M. Adorf, “Towards HST restoration with space-variant PSF, cosmic rays and other missing data,” in The Restoration of HST Images and Spectra II, R. J. Hanisch and R. L. White, eds., pp. 72–78 (1994).
J. G. Nagy and D. P. O’Leary, “Fast iterative image restoration with a spatially varying PSF,” in Advanced Signal Processing Algorithms, Architectures, and Implementations VII, F. T. Luk, ed., vol. 3162, pp. 388–399 (SPIE, 1997).
H. W. Engl, M. Hanke, and A. Neubauer, Regularization of Inverse Problems (Kluwer Academic Publishers, Dordrecht, 2000).
P. C. Hansen, Rank-deficient and discrete ill-posed problems (SIAM, Philadelphia, PA, 1997).
C. R. Vogel, Computational Methods for Inverse Problems (SIAM, Philadelphia, PA, 2002).
[Crossref]