The Effect of the Ill-posed Problem on Quantitative Error Assessment in Digital Image Correlation
Abstract
Here, this work explores the effect of the ill-posed problem on uncertainty quantification for motion estimation using digital image correlation (DIC) (Sutton et al. 2009). We develop a correction factor for standard uncertainty estimates based on the cosine of the angle between the true motion and the image gradients, in an integral sense over a subregion of the image. This correction factor accounts for variability in the DIC solution previously unaccounted for when considering only image noise, interpolation bias, contrast, and the software settings such as subset size and spacing.
- Authors:
-
- Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Center for Computing Research
- Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Diagnostic Science & Engineering
- Publication Date:
- Research Org.:
- Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
- Sponsoring Org.:
- USDOE National Nuclear Security Administration (NNSA)
- OSTI Identifier:
- 1421608
- Report Number(s):
- SAND-2017-5602J
Journal ID: ISSN 0014-4851; PII: 360
- Grant/Contract Number:
- AC04-94AL85000; NA0003525
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Experimental Mechanics
- Additional Journal Information:
- Journal Volume: 2017; Journal ID: ISSN 0014-4851
- Publisher:
- Springer
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 97 MATHEMATICS AND COMPUTING; Digital image correlation; Uncertainty quantification; Spatial resolution; Error estimates; Ill-posed inverse problems
Citation Formats
Lehoucq, R. B., Reu, P. L., and Turner, D. Z. The Effect of the Ill-posed Problem on Quantitative Error Assessment in Digital Image Correlation. United States: N. p., 2017.
Web. doi:10.1007/s11340-017-0360-5.
Lehoucq, R. B., Reu, P. L., & Turner, D. Z. The Effect of the Ill-posed Problem on Quantitative Error Assessment in Digital Image Correlation. United States. https://doi.org/10.1007/s11340-017-0360-5
Lehoucq, R. B., Reu, P. L., and Turner, D. Z. Mon .
"The Effect of the Ill-posed Problem on Quantitative Error Assessment in Digital Image Correlation". United States. https://doi.org/10.1007/s11340-017-0360-5. https://www.osti.gov/servlets/purl/1421608.
@article{osti_1421608,
title = {The Effect of the Ill-posed Problem on Quantitative Error Assessment in Digital Image Correlation},
author = {Lehoucq, R. B. and Reu, P. L. and Turner, D. Z.},
abstractNote = {Here, this work explores the effect of the ill-posed problem on uncertainty quantification for motion estimation using digital image correlation (DIC) (Sutton et al. 2009). We develop a correction factor for standard uncertainty estimates based on the cosine of the angle between the true motion and the image gradients, in an integral sense over a subregion of the image. This correction factor accounts for variability in the DIC solution previously unaccounted for when considering only image noise, interpolation bias, contrast, and the software settings such as subset size and spacing.},
doi = {10.1007/s11340-017-0360-5},
journal = {Experimental Mechanics},
number = ,
volume = 2017,
place = {United States},
year = {Mon Nov 27 00:00:00 EST 2017},
month = {Mon Nov 27 00:00:00 EST 2017}
}
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A motion blur compensation algorithm for 2D DIC measurements of deformable bodies
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Rendering Deformed Speckle Images with a Boolean Model
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