2001
DOI: 10.1364/ol.26.001831
|View full text |Cite
|
Sign up to set email alerts
|

Effective noise in thresholded intensity distribution: influence on centroid statistics

Abstract: It is usual to preprocess data before reduction, but it is not so common to study how this operation affects the final results. Determination of the centroid is a relevant task for many optical measurement devices, and the centroid is very often calculated over thresholded data. The influence of preprocessing thresholding algorithms on the statistical properties of intensity data affected by additive Gaussian noise is described as a different effective additive signal perturbation. Theoretical, simulated, and … Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

0
10
0

Year Published

2008
2008
2018
2018

Publication Types

Select...
8
1

Relationship

1
8

Authors

Journals

citations
Cited by 18 publications
(10 citation statements)
references
References 2 publications
0
10
0
Order By: Relevance
“…A threshold cut was not used, as the threshold operation can introduce errors when data points are close to the threshold level [32]. Instead, a window of points was taken.…”
Section: Resultsmentioning
confidence: 99%
“…A threshold cut was not used, as the threshold operation can introduce errors when data points are close to the threshold level [32]. Instead, a window of points was taken.…”
Section: Resultsmentioning
confidence: 99%
“…There is also an extrinsic fluctuation contributing to the measured changes, due to random eye movements, different initial pupil positioning between measurement series (Davies et al. , 2003), and measurement noise due to the centroiding algorithms and the detector noise (Ares and Arines, 2001, 2004). Our results (see ) show that there is a high inter‐series variability of aberrations for a fixed gaze, which diminishes the signal‐to‐noise ratio for the detection of gaze‐related aberration changes.…”
Section: Discussionmentioning
confidence: 99%
“…[12][13][14][15][16] The thresholding method is the operation on the continuous intensity distribution I x,y as a nonlinear transformation to Iu x,y described in Eq. 1.…”
Section: Thresholding Algorithmmentioning
confidence: 99%