2021
DOI: 10.1364/ao.426162
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2D zonal integration with unordered data

Abstract: Numerical integration of two-dimensional gradient data is an important step for many slope-measuring optical instruments. However, existing methods are limited by low accuracy or data location restrictions. The zonal integration algorithm in this paper is a generalized process that works with unordered data via Taylor series approximations of finite difference calculations. This method does not require iteration, and all significant steps rely on matrix calculations for a least-squares solution. Simultaneous i… Show more

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Cited by 5 publications
(2 citation statements)
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“…Any integration method effectively operates at the level of larger or smaller surface patches. Therefore, small errors in the DM or regularization data, sampling grid properties (Leung and Cai, 2020;Smith, 2021), or the influence of the tested surface itself Niu et al, 2021) may have a global effect on the reconstruction outcomes, and deviations from the true shape end up correlated at different scales (Pouya Fard and Davies, 2018). While we are not aware of a general method to predict integration uncertainties in DM, it is clear that simple Advanced Optical Technologies frontiersin.org quality metrics adopted, e.g., in fringe projection or laser triangulation such as "RMS height error" do not capture the statistics of errors inherent for DM.…”
Section: Integration/interpolation Biasesmentioning
confidence: 99%
“…Any integration method effectively operates at the level of larger or smaller surface patches. Therefore, small errors in the DM or regularization data, sampling grid properties (Leung and Cai, 2020;Smith, 2021), or the influence of the tested surface itself Niu et al, 2021) may have a global effect on the reconstruction outcomes, and deviations from the true shape end up correlated at different scales (Pouya Fard and Davies, 2018). While we are not aware of a general method to predict integration uncertainties in DM, it is clear that simple Advanced Optical Technologies frontiersin.org quality metrics adopted, e.g., in fringe projection or laser triangulation such as "RMS height error" do not capture the statistics of errors inherent for DM.…”
Section: Integration/interpolation Biasesmentioning
confidence: 99%
“…Any integration method effectively operates at the level of larger or smaller surface patches. Therefore, small errors in the DM or regularization data, sampling grid properties [328], or the influence of the tested surface itself [329,330] may have a global effect on the reconstruction outcomes, and deviations from the true shape end up correlated at different scales [331]. While we are not aware of a general method to predict integration uncertainties in DM, it is clear that simple quality metrics adopted e.g.…”
Section: Integration/interpolation Biasesmentioning
confidence: 99%