A newly proposed algorithm named single pixel evaluation (SPE) has been developed to increase the resolution of micro-PIV to its physical limit of one pixel. Despite the SPE is able to improve the resolution significantly in comparison with conventional cross-correlation, some phenomenon are still unknown due to its infancy, resulting in discrepancies between the analytic predictions and the experimental measurements. To provide reliable rules as applying the SPE, an overall inspection of the algorithm's behaviors is essential. This paper investigated five general factors, determining their performances via synthetic particle images subjected to a parabolic flow profile. The factors include particle image quality, particle image density, search radius (SR), particle image displacement, and particle image diameter. The results indicate that the particle image quality behaves the most significantly among the factors. Moreover, the SPE was also compared with the fast Fourier transform based cross-correlation (FFT-CC) under the equivalent signal-to-noise ratio (SNR). The tendencies of optimal values with respect to different factors are revealed in the following text. To complete the study, experiments on a straight microchannel were implemented to verify the observations from the simulations. The measured images which followed the suggested rules show better results than the other ones.

1.
Chen
J
,
Katz
J
(
2005
)
Elimination of peak-locking error in PIV analysis using the correlation mapping method
.
Meas. Sci. Technol
.
16
:
1605
1618
.
2.
Fincham
AM
,
Spedding
GR
(
1997
),
Low cost, high resolution DPIV for measurement of turbulent fluid flow
.
Exp. Fluids
23
:
449
462
.
3.
Gui
L
,
Wereley
ST
(
2002
),
A correlation-based continuous window-shift technique to reduce the peak-locking effect in digital PIV image evaluation
.
Exp. Fluids
32
:
506
517
.
4.
Huang
H
,
Diabiri
D
,
Gharib
M
(
1997
),
On the error of digital particle image velocimetry
.
Meas. Sci. Technol.
8
:
1427
1440
.
5.
Meinhart
CD
,
Wereley
ST
,
Santiago
JG
(
1999
),
PIV measurements of a microchannel flow
.
Exp. Fluids
27
:
414
419
.
6.
Meinhart
CD
,
Wereley
ST
,
Santiago
JG
(
2000
),
A PIV Algorithm for Estimating Time-Averaged Velocity Fields
.
Journal of Fluids Engineering
122
:
285
289
.
7.
Prasad
K
,
Adrian
RJ
,
Landreth
CC
,
Offutt
PW
(
1992
),
Effect of resolution on the speed and accuracy of particle image velocimetry interrogation
.
Exp. Fluids
13
:
105
116
.
8.
Santiago
JG
,
Wereley
ST
,
Meinhart
CD
,
Beebe
DJ
,
Adrian
RJ
(
1998
),
A particle image velocimetry system for microfluidics
.
Exp. Fluids
25
:
316
319
.
9.
Sud, A. (2005), Nano-Velocimetry: Single Pixel Evaluation for Particle Image Velocimetry, Thesis, Purdue University.
10.
Wereley ST, Meinhart CD, Gui L, Tretheway D, Sud A (2005) Single Pixel Evaluation of Microchannel Flows. Proceeding of IMECE2005, November 5–11, 2005, Orlando, Florida USA.
11.
Westerweel
J
(
1997
),
Fundamentals of digital particle image velocimetry
.
Meas. Sci. Technol.
8
:
1379
1392
.
12.
Westerweel
J
,
Geelhoed
PF
,
Lindken
R
(
2004
),
Single-pixel resolution ensemble correlation for micro-PIV applications
.
Exp. Fluids
37
:
375
384
.
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