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
Original Manuscript: July 15, 1992
Revised Manuscript: October 22, 1992
Manuscript Accepted: December 9, 1992
Published: May 1, 1993
Timothy J. Schulz, "Multiframe blind deconvolution of astronomical images," J. Opt. Soc. Am. A 10, 1064-1073 (1993)