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Article: Acceleration of autofocusing with improved edge extraction using structure tensor and Schatten norm

TitleAcceleration of autofocusing with improved edge extraction using structure tensor and Schatten norm
Authors
KeywordsCoherent imaging
Computation speed
Digital holography
Edge extraction
Imaging modality
Issue Date2020
PublisherOptical Society of America: Open Access Journals. The Journal's web site is located at http://www.opticsexpress.org
Citation
Optics Express, 2020, v. 28 n. 10, p. 14712-14728 How to Cite?
AbstractDetermining the optimal focal plane amongst a stack of blurred images in a short response time is a non-trivial task in optical imaging like microscopy and photography. An autofocusing algorithm, or in other words, a focus metric, is key to effectively dealing with such problem. In previous work, we proposed a structure tensor-based autofocusing algorithm for coherent imaging, i.e., digital holography. In this paper, we further extend the realm of this method in more imaging modalities. With an optimized computation scheme of structure tensor, a significant acceleration of about fivefold in computation speed without sacrificing the autofocusing accuracy is achieved by using the Schatten matrix norm instead of the vector norm. Besides, we also demonstrate its edge extraction capability by retrieving the intermediate tensor image. Synthesized and experimental data acquired in various imaging scenarios such as incoherent microscopy and photography are demonstrated to verify the efficacy of this method.
Persistent Identifierhttp://hdl.handle.net/10722/287649
ISSN
2023 Impact Factor: 3.2
2023 SCImago Journal Rankings: 0.998
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorREN, Z-
dc.contributor.authorLam, EY-
dc.contributor.authorZhao, J-
dc.date.accessioned2020-10-05T12:01:12Z-
dc.date.available2020-10-05T12:01:12Z-
dc.date.issued2020-
dc.identifier.citationOptics Express, 2020, v. 28 n. 10, p. 14712-14728-
dc.identifier.issn1094-4087-
dc.identifier.urihttp://hdl.handle.net/10722/287649-
dc.description.abstractDetermining the optimal focal plane amongst a stack of blurred images in a short response time is a non-trivial task in optical imaging like microscopy and photography. An autofocusing algorithm, or in other words, a focus metric, is key to effectively dealing with such problem. In previous work, we proposed a structure tensor-based autofocusing algorithm for coherent imaging, i.e., digital holography. In this paper, we further extend the realm of this method in more imaging modalities. With an optimized computation scheme of structure tensor, a significant acceleration of about fivefold in computation speed without sacrificing the autofocusing accuracy is achieved by using the Schatten matrix norm instead of the vector norm. Besides, we also demonstrate its edge extraction capability by retrieving the intermediate tensor image. Synthesized and experimental data acquired in various imaging scenarios such as incoherent microscopy and photography are demonstrated to verify the efficacy of this method.-
dc.languageeng-
dc.publisherOptical Society of America: Open Access Journals. The Journal's web site is located at http://www.opticsexpress.org-
dc.relation.ispartofOptics Express-
dc.rightsOptics Express. Copyright © Optical Society of America: Open Access Journals.-
dc.rights© 2020 [Optical Society of America]. Users may use, reuse, and build upon the article, or use the article for text or data mining, so long as such uses are for non-commercial purposes and appropriate attribution is maintained. All other rights are reserved.-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.subjectCoherent imaging-
dc.subjectComputation speed-
dc.subjectDigital holography-
dc.subjectEdge extraction-
dc.subjectImaging modality-
dc.titleAcceleration of autofocusing with improved edge extraction using structure tensor and Schatten norm-
dc.typeArticle-
dc.identifier.emailLam, EY: elam@eee.hku.hk-
dc.identifier.authorityLam, EY=rp00131-
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1364/OE.392544-
dc.identifier.pmid32403507-
dc.identifier.scopuseid_2-s2.0-85084389004-
dc.identifier.hkuros314915-
dc.identifier.volume28-
dc.identifier.issue10-
dc.identifier.spage14712-
dc.identifier.epage14728-
dc.identifier.isiWOS:000538870000047-
dc.publisher.placeUnited States-
dc.identifier.issnl1094-4087-

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