Reconfigurable rainbow PIV for 3D flow measurement

Jinhui Xiong*, Qiang Fu, Ramzi Idoughi, Wolfgang Heidrich

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

15 Scopus citations


In recent years, 3D Particle Imaging Velocimetry (PIV) has become more and more attractive due to its ability to fully characterize various fluid flows. However, 3D fluid capture and velocity field reconstruction remain a challenging problem. A recent rainbow PIV system encodes depth into color and successfully recovers 3D particle trajectories, but it also suffers from a limited and fixed volume size, as well as a relatively low light efficiency. In this paper, we propose a reconfigurable rainbow PIV system that extends the volume size to a considerable range. We introduce a parallel double-grating system to improve the light efficiency for scalable rainbow generation. A varifocal encoded diffractive lens is designed to accommodate the size of the rainbow illumination, ranging from 15 mm to 50 mm. We also propose a truncated consensus ADMM algorithm to efficiently reconstruct particle locations. Our algorithm is 5x faster compared to the state-of-the-art. The reconstruction quality is also improved significantly for a series of density levels. Our method is demonstrated by both simulation and experimental results.

Original languageEnglish (US)
Title of host publicationIEEE International Conference on Computational Photography, ICCP 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages9
ISBN (Electronic)9781538625262
StatePublished - May 29 2018
Event2018 IEEE International Conference on Computational Photography, ICCP 2018 - Pittsburgh, United States
Duration: May 4 2018May 6 2018

Publication series

NameIEEE International Conference on Computational Photography, ICCP 2018


Conference2018 IEEE International Conference on Computational Photography, ICCP 2018
Country/TerritoryUnited States

Bibliographical note

Publisher Copyright:
© 2018 IEEE.

ASJC Scopus subject areas

  • Computational Mathematics
  • Signal Processing
  • Atomic and Molecular Physics, and Optics


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