Abstract

Maximum-likelihood estimation techniques are presented for the problem of forming object estimates from turbulence-degraded images when the point-spread functions are unknown. The inability of unconstrained maximum-likelihood methods to form meaningful estimates is acknowledged, and iterative algorithms are derived for estimating the object by using both a penalized maximum-likelihood method and a physically meaningful parameterization of the point-spread functions by phase errors distributed over an aperture.

© 1993 Optical Society of America

Full Article  |  PDF Article
OSA Recommended Articles
Multiframe blind deconvolution of heavily blurred astronomical images

Yulia V. Zhulina
Appl. Opt. 45(28) 7342-7352 (2006)

Segmentation-based multiframe blind deconvolution of solar images

Noriaki Miura and Naoshi Baba
J. Opt. Soc. Am. A 12(9) 1858-1866 (1995)

Fast and optimal multiframe blind deconvolution algorithm for high-resolution ground-based imaging of space objects

Charles L. Matson, Kathy Borelli, Stuart Jefferies, Charles C. Beckner, Jr., E. Keith Hege, and Michael Lloyd-Hart
Appl. Opt. 48(1) A75-A92 (2009)

References

You do not have subscription access to this journal. Citation lists with outbound citation links are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access OSA Member Subscription

Cited By

You do not have subscription access to this journal. Cited by links are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access OSA Member Subscription

Figures (3)

You do not have subscription access to this journal. Figure files are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access OSA Member Subscription

Equations (53)

You do not have subscription access to this journal. Equations are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access OSA Member Subscription

Metrics

You do not have subscription access to this journal. Article level metrics are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access OSA Member Subscription