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Versatile optimization-based speed-up method for autofocusing in digital holographic microscopy

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Versatile optimization-based speed-up method for autofocusing in digital holographic microscopy

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dc.contributor.author	Winnik, Julianna
dc.contributor.author	Suski, Damian
dc.contributor.author	Zdankowski, Piotr
dc.contributor.author	Stanaszek, Luiza
dc.contributor.author	Trusiak, Maciej
dc.contributor.author	Micó Serrano, Vicente
dc.date.accessioned	2023-06-22T16:06:49Z
dc.date.available	2023-06-22T16:06:49Z
dc.date.issued	2021
dc.identifier.citation	Winnik, Julianna Suski, Damian Zdankowski, Piotr Stanaszek, Luiza Trusiak, Maciej Mico Serrano, Vicente 2021 Versatile optimization-based speed-up method for autofocusing in digital holographic microscopy Optics Express 29 21 33297 33311
dc.identifier.uri	https://hdl.handle.net/10550/88515
dc.description.abstract	We propose a speed-up method for the in-focus plane detection in digital holographic microscopy that can be applied to a broad class of autofocusing algorithms that involve repetitive propagation of an object wave to various axial locations to decide the in-focus position. The classical autofocusing algorithms apply a uniform search strategy, i.e., they probe multiple, uniformly distributed axial locations, which leads to heavy computational overhead. Our method substantially reduces the computational load, without sacrificing the accuracy, by skillfully selecting the next location to investigate, which results in a decreased total number of probed propagation distances. This is achieved by applying the golden selection search with parabolic interpolation, which is the gold standard for tackling single-variable optimization problems. The proposed approach is successfully applied to three diverse autofocusing cases, providing up to 136-fold speed-up.
dc.language.iso	eng
dc.relation.ispartof	Optics Express, 2021, vol. 29, num. 21, p. 33297-33311
dc.subject	Òptica
dc.title	Versatile optimization-based speed-up method for autofocusing in digital holographic microscopy
dc.type	journal article
dc.date.updated	2023-06-22T16:06:49Z
dc.identifier.doi	10.1364/OE.438496
dc.identifier.idgrec	160530
dc.rights.accessRights	open access