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An Optical Flow Algorithm with Automatic Parameter Adjustment for Fluid Velocimetry Cover

An Optical Flow Algorithm with Automatic Parameter Adjustment for Fluid Velocimetry

Open Access
|Oct 2025

Figures & Tables

Figure 1

Velocity magnitude estimated at a instant using (b) wOFV and (c) cross-correlation, compared to the (a) ground truth from DNS.

Figure 2

Normalized RMSE of the (a) velocity field and (b) vorticity field obtained using cross-correlation compared to the presented software (wOFV).

Figure 3

Normalized RMSE of the velocity fields obtained using different open-source software compared with the software presented (wOFV).

Figure 4

Schematic of the core code workflow.

Figure 5

Schematic explanation of image patching.

Figure 6

Magnitude of the velocity estimates obtained using the same particle image data processed at a patch size of 642, 1282, and 2562 pixels.

Figure 7

Schematic explanation of image pyramiding scheme

Figure 8

Magnitude of the velocity estimates obtained using the same particle image data processed at a final pyramid level of j = 1 and j = 2, compared to the DNS ground truth.

Figure 9

The effect of different values of η on the estimated velocity field.

Figure 10

An illustration of the image warping operation.

Figure 11

Magnitude of the velocity field computed from the same PIV data processed at the same settings, with (c) and without (b) a Gaussian filter applied to the particle images at each pyramid level, compared to the ground truth (a).

Figure 12

An depiction of computing JDCC and JRCC to estimate η.

Pseudo-code 1

RunMain

Pseudo-code 2

BayesPyd_Sub

Pseudo-code 3

BayesPyd_Sub

DOI: https://doi.org/10.5334/jors.584 | Journal eISSN: 2049-9647
Language: English
Submitted on: May 22, 2025
Accepted on: Jul 18, 2025
Published on: Oct 13, 2025
Published by: Ubiquity Press
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year

© 2025 Gauresh Raj Jassal, William Thielicke, Bryan E. Schmidt, published by Ubiquity Press
This work is licensed under the Creative Commons Attribution 4.0 License.