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Quantifying the spatial resolution of the maximum a posteriori estimate in linear, rank-deficient, Bayesian hard field tomography

Emmert, Johannes ; Wagner, Steven ; Daun, Kyle J. (2021)
Quantifying the spatial resolution of the maximum a posteriori estimate in linear, rank-deficient, Bayesian hard field tomography.
In: Measurement Science and Technology, 2021, 32 (2)
doi: 10.26083/tuprints-00019337
Artikel, Zweitveröffentlichung, Verlagsversion

Kurzbeschreibung (Abstract)

Image based diagnostics are interpreted in the context of spatial resolution. The same is true for tomographic image reconstruction. Current empirically driven approaches to quantify spatial resolution in chemical species tomography rely on a deterministic formulation based on point-spread functions which neglect the statistical prior information, that is integral to rank-deficient tomography. We propose a statistical spatial resolution measure based on the covariance of the reconstruction (point estimate). By demonstrating the resolution measure on a chemical species tomography test case, we show that the prior information acts as a lower limit for the spatial resolution. Furthermore, the spatial resolution measure can be employed for designing tomographic systems under consideration of spatial inhomogeneity of spatial resolution.

Typ des Eintrags: Artikel
Erschienen: 2021
Autor(en): Emmert, Johannes ; Wagner, Steven ; Daun, Kyle J.
Art des Eintrags: Zweitveröffentlichung
Titel: Quantifying the spatial resolution of the maximum a posteriori estimate in linear, rank-deficient, Bayesian hard field tomography
Sprache: Englisch
Publikationsjahr: 2021
Publikationsdatum der Erstveröffentlichung: 2021
Verlag: IOP Publishing
Titel der Zeitschrift, Zeitung oder Schriftenreihe: Measurement Science and Technology
Jahrgang/Volume einer Zeitschrift: 32
(Heft-)Nummer: 2
Kollation: 10 Seiten
DOI: 10.26083/tuprints-00019337
URL / URN: https://tuprints.ulb.tu-darmstadt.de/19337
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Herkunft: Zweitveröffentlichung aus gefördertem Golden Open Access
Kurzbeschreibung (Abstract):

Image based diagnostics are interpreted in the context of spatial resolution. The same is true for tomographic image reconstruction. Current empirically driven approaches to quantify spatial resolution in chemical species tomography rely on a deterministic formulation based on point-spread functions which neglect the statistical prior information, that is integral to rank-deficient tomography. We propose a statistical spatial resolution measure based on the covariance of the reconstruction (point estimate). By demonstrating the resolution measure on a chemical species tomography test case, we show that the prior information acts as a lower limit for the spatial resolution. Furthermore, the spatial resolution measure can be employed for designing tomographic systems under consideration of spatial inhomogeneity of spatial resolution.

Status: Verlagsversion
URN: urn:nbn:de:tuda-tuprints-193374
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Keywords: resolution, tomography, bayesian inference, absorption spectroscopy, spatial resolution

Sachgruppe der Dewey Dezimalklassifikatin (DDC): 600 Technik, Medizin, angewandte Wissenschaften > 600 Technik
Fachbereich(e)/-gebiet(e): 16 Fachbereich Maschinenbau
16 Fachbereich Maschinenbau > Fachgebiet Reaktive Strömungen und Messtechnik (RSM)
Hinterlegungsdatum: 23 Aug 2021 12:16
Letzte Änderung: 31 Aug 2021 05:23
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