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Maximum-likelihood estimation of parameterized wavefronts from multifocal data

A method for determining the pupil phase distribution of an optical system is demonstrated. Coefficients in a wavefront expansion were estimated using likelihood methods, where the data consisted of multiple irradiance patterns near focus. Proof-of-principle results were obtained in both simulation...

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Detalles Bibliográficos
Autores principales: Sakamoto, Julia A., Barrett, Harrison H.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Optical Society of America 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3601653/
https://www.ncbi.nlm.nih.gov/pubmed/22772282
http://dx.doi.org/10.1364/OE.20.015928
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author Sakamoto, Julia A.
Barrett, Harrison H.
author_facet Sakamoto, Julia A.
Barrett, Harrison H.
author_sort Sakamoto, Julia A.
collection PubMed
description A method for determining the pupil phase distribution of an optical system is demonstrated. Coefficients in a wavefront expansion were estimated using likelihood methods, where the data consisted of multiple irradiance patterns near focus. Proof-of-principle results were obtained in both simulation and experiment. Large-aberration wavefronts were handled in the numerical study. Experimentally, we discuss the handling of nuisance parameters. Fisher information matrices, Cramér-Rao bounds, and likelihood surfaces are examined. ML estimates were obtained by simulated annealing to deal with numerous local extrema in the likelihood function. Rapid processing techniques were employed to reduce the computational time.
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spelling pubmed-36016532013-06-28 Maximum-likelihood estimation of parameterized wavefronts from multifocal data Sakamoto, Julia A. Barrett, Harrison H. Opt Express Research-Article A method for determining the pupil phase distribution of an optical system is demonstrated. Coefficients in a wavefront expansion were estimated using likelihood methods, where the data consisted of multiple irradiance patterns near focus. Proof-of-principle results were obtained in both simulation and experiment. Large-aberration wavefronts were handled in the numerical study. Experimentally, we discuss the handling of nuisance parameters. Fisher information matrices, Cramér-Rao bounds, and likelihood surfaces are examined. ML estimates were obtained by simulated annealing to deal with numerous local extrema in the likelihood function. Rapid processing techniques were employed to reduce the computational time. Optical Society of America 2012-06-28 /pmc/articles/PMC3601653/ /pubmed/22772282 http://dx.doi.org/10.1364/OE.20.015928 Text en ©2012 Optical Society of America http://creativecommons.org/licenses/by-nc-nd/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 Unported License, which permits download and redistribution, provided that the original work is properly cited. This license restricts the article from being modified or used commercially.
spellingShingle Research-Article
Sakamoto, Julia A.
Barrett, Harrison H.
Maximum-likelihood estimation of parameterized wavefronts from multifocal data
title Maximum-likelihood estimation of parameterized wavefronts from multifocal data
title_full Maximum-likelihood estimation of parameterized wavefronts from multifocal data
title_fullStr Maximum-likelihood estimation of parameterized wavefronts from multifocal data
title_full_unstemmed Maximum-likelihood estimation of parameterized wavefronts from multifocal data
title_short Maximum-likelihood estimation of parameterized wavefronts from multifocal data
title_sort maximum-likelihood estimation of parameterized wavefronts from multifocal data
topic Research-Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3601653/
https://www.ncbi.nlm.nih.gov/pubmed/22772282
http://dx.doi.org/10.1364/OE.20.015928
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