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
Article, Secondary publication, Publisher's Version
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Item Type: | Article |
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Type of entry: | Secondary publication |
Title: | Quantifying the spatial resolution of the maximum a posteriori estimate in linear, rank-deficient, Bayesian hard field tomography |
Language: | English |
Date: | 23 August 2021 |
Place of Publication: | Darmstadt |
Year of primary publication: | 2021 |
Publisher: | IOP Publishing |
Journal or Publication Title: | Measurement Science and Technology |
Volume of the journal: | 32 |
Issue Number: | 2 |
Collation: | 10 Seiten |
DOI: | 10.26083/tuprints-00019337 |
Corresponding Links: | |
Origin: | Secondary publication via sponsored Golden Open Access |
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: | Publisher's Version |
URN: | urn:nbn:de:tuda-tuprints-193374 |
Additional Information: | Keywords: resolution, tomography, bayesian inference, absorption spectroscopy, spatial resolution |
Classification DDC: | 600 Technology, medicine, applied sciences > 600 Technology |
Divisions: | 16 Department of Mechanical Engineering > Institute of Reactive Flows and Diagnostics (RSM) |
Date Deposited: | 23 Aug 2021 12:16 |
Last Modified: | 05 Dec 2024 16:17 |
URI: | https://tuprints.ulb.tu-darmstadt.de/id/eprint/19337 |
PPN: | 484668706 |
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