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
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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 |
| Zugehörige Links: | |
| 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 |
| Zusätzliche Informationen: | 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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| Suche nach Titel in: | TUfind oder in Google |
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- Quantifying the spatial resolution of the maximum a posteriori estimate in linear, rank-deficient, Bayesian hard field tomography. (deposited 23 Aug 2021 12:16) [Gegenwärtig angezeigt]
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