Dynamic granularity of imaging systems
Abstract
Imaging systems that include a specific source, imaging concept, geometry, and detector have unique properties such as signal-to-noise ratio, dynamic range, spatial resolution, distortions, and contrast. Some of these properties are inherently connected, particularly dynamic range and spatial resolution. It must be emphasized that spatial resolution is not a single number but must be seen in the context of dynamic range and consequently is better described by a function or distribution. We introduce the “dynamic granularity” Gdyn as a standardized, objective relation between a detector’s spatial resolution (granularity) and dynamic range for complex imaging systems in a given environment rather than the widely found characterization of detectors such as cameras or films by themselves. We found that this relation can partly be explained through consideration of the signal’s photon statistics, background noise, and detector sensitivity, but a comprehensive description including some unpredictable data such as dust, damages, or an unknown spectral distribution will ultimately have to be based on measurements. Measured dynamic granularities can be objectively used to assess the limits of an imaging system’s performance including all contributing noise sources and to qualify the influence of alternative components within an imaging system. Our article explains the construction criteria tomore »
- Authors:
-
- Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
- Publication Date:
- Research Org.:
- Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
- Sponsoring Org.:
- USDOE National Nuclear Security Administration (NNSA)
- OSTI Identifier:
- 1236211
- Report Number(s):
- SAND-2015-8748J
Journal ID: ISSN 0034-6748; RSINAK; 615286
- Grant/Contract Number:
- AC04-94AL85000
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Review of Scientific Instruments
- Additional Journal Information:
- Journal Volume: 86; Journal Issue: 11; Journal ID: ISSN 0034-6748
- Publisher:
- American Institute of Physics (AIP)
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND TECHNOLOGY; image sensors; photons; spatial resolution; x-ray detectors; granular systems; imaging; contrast
Citation Formats
Geissel, Matthias, Smith, Ian C., Shores, Jonathon E., and Porter, John L. Dynamic granularity of imaging systems. United States: N. p., 2015.
Web. doi:10.1063/1.4934543.
Geissel, Matthias, Smith, Ian C., Shores, Jonathon E., & Porter, John L. Dynamic granularity of imaging systems. United States. https://doi.org/10.1063/1.4934543
Geissel, Matthias, Smith, Ian C., Shores, Jonathon E., and Porter, John L. Wed .
"Dynamic granularity of imaging systems". United States. https://doi.org/10.1063/1.4934543. https://www.osti.gov/servlets/purl/1236211.
@article{osti_1236211,
title = {Dynamic granularity of imaging systems},
author = {Geissel, Matthias and Smith, Ian C. and Shores, Jonathon E. and Porter, John L.},
abstractNote = {Imaging systems that include a specific source, imaging concept, geometry, and detector have unique properties such as signal-to-noise ratio, dynamic range, spatial resolution, distortions, and contrast. Some of these properties are inherently connected, particularly dynamic range and spatial resolution. It must be emphasized that spatial resolution is not a single number but must be seen in the context of dynamic range and consequently is better described by a function or distribution. We introduce the “dynamic granularity” Gdyn as a standardized, objective relation between a detector’s spatial resolution (granularity) and dynamic range for complex imaging systems in a given environment rather than the widely found characterization of detectors such as cameras or films by themselves. We found that this relation can partly be explained through consideration of the signal’s photon statistics, background noise, and detector sensitivity, but a comprehensive description including some unpredictable data such as dust, damages, or an unknown spectral distribution will ultimately have to be based on measurements. Measured dynamic granularities can be objectively used to assess the limits of an imaging system’s performance including all contributing noise sources and to qualify the influence of alternative components within an imaging system. Our article explains the construction criteria to formulate a dynamic granularity and compares measured dynamic granularities for different detectors used in the X-ray backlighting scheme employed at Sandia’s Z-Backlighter facility.},
doi = {10.1063/1.4934543},
journal = {Review of Scientific Instruments},
number = 11,
volume = 86,
place = {United States},
year = {Wed Nov 04 00:00:00 EST 2015},
month = {Wed Nov 04 00:00:00 EST 2015}
}
Web of Science
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Works referencing / citing this record:
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