Extended scene deep learning wavefront sensing

Bas de Bruijne; Gleb Vdovin; Oleg Soloviev

doi:10.1364/JOSAA.443436

Extended scene deep learning wavefront sensing

Bas de Bruijne^*, Gleb Vdovin, Oleg Soloviev

^*Corresponding author for this work

Research output: Contribution to journal › Article › Scientific › peer-review

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Abstract

We have applied a combination of blind deconvolution and deep learning to the processing of Shack-Hartmann images.By using the intensity information contained in spot positions, and the fine structure of the separate images created by the lenslets,we have increased the sensitivity and resolution of the sensor over the limit defined by standard processing of spot displacements only.We also have demonstrated the applicability of the method to wavefront sensing using extended objects as a reference.

Original language	English
Pages (from-to)	621-627
Journal	Journal of the Optical Society of America A: Optics and Image Science, and Vision
Volume	39
Issue number	4
DOIs	https://doi.org/10.1364/JOSAA.443436
Publication status	Published - 2022

Bibliographical note

Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care
Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

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title = "Extended scene deep learning wavefront sensing",

abstract = "We have applied a combination of blind deconvolution and deep learning to the processing of Shack-Hartmann images.By using the intensity information contained in spot positions, and the fine structure of the separate images created by the lenslets,we have increased the sensitivity and resolution of the sensor over the limit defined by standard processing of spot displacements only.We also have demonstrated the applicability of the method to wavefront sensing using extended objects as a reference. ",

author = "{de Bruijne}, Bas and Gleb Vdovin and Oleg Soloviev",

note = "Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.",

year = "2022",

doi = "10.1364/JOSAA.443436",

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AU - de Bruijne, Bas

AU - Vdovin, Gleb

AU - Soloviev, Oleg

N1 - Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

PY - 2022

Y1 - 2022

N2 - We have applied a combination of blind deconvolution and deep learning to the processing of Shack-Hartmann images.By using the intensity information contained in spot positions, and the fine structure of the separate images created by the lenslets,we have increased the sensitivity and resolution of the sensor over the limit defined by standard processing of spot displacements only.We also have demonstrated the applicability of the method to wavefront sensing using extended objects as a reference.

AB - We have applied a combination of blind deconvolution and deep learning to the processing of Shack-Hartmann images.By using the intensity information contained in spot positions, and the fine structure of the separate images created by the lenslets,we have increased the sensitivity and resolution of the sensor over the limit defined by standard processing of spot displacements only.We also have demonstrated the applicability of the method to wavefront sensing using extended objects as a reference.

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JF - Journal of the Optical Society of America A: Optics and Image Science, and Vision

SN - 1084-7529

IS - 4

ER -

Extended scene deep learning wavefront sensing

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