TU Darmstadt / ULB / TUbiblio

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. (Publisher's Version)
In: Measurement Science and Technology, 32 (2), IOP Publishing, ISSN 0957-0233, e-ISSN 1361-6501,
DOI: 10.26083/tuprints-00019337,
[Article]

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.

Item Type: Article
Erschienen: 2021
Creators: Emmert, Johannes ; Wagner, Steven ; Daun, Kyle J.
Origin: Secondary publication via sponsored Golden Open Access
Status: Publisher's Version
Title: Quantifying the spatial resolution of the maximum a posteriori estimate in linear, rank-deficient, Bayesian hard field tomography
Language: English
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.

Journal or Publication Title: Measurement Science and Technology
Journal volume: 32
Number: 2
Publisher: IOP Publishing
Collation: 10 Seiten
Divisions: 16 Department of Mechanical Engineering
16 Department of Mechanical Engineering > Institute of Reactive Flows and Diagnostics (RSM)
Date Deposited: 23 Aug 2021 12:16
DOI: 10.26083/tuprints-00019337
Official URL: https://tuprints.ulb.tu-darmstadt.de/19337
URN: urn:nbn:de:tuda-tuprints-193374
Additional Information:

Keywords: resolution, tomography, bayesian inference, absorption spectroscopy, spatial resolution

Corresponding Links:
Export:
Suche nach Titel in: TUfind oder in Google
Send an inquiry Send an inquiry

Options (only for editors)
Show editorial Details Show editorial Details