Self-correction of the optical distortion effect of thermal plumes in particle image velocimetry

Optical distortion caused by changes in the refractive index of fluid flow is a common issue in flow visualization using techniques, such as particle image velocimetry (PIV). In thermally driven convection, this distortion can severely interfere with PIV results due to the ubiquitous density and, therefore, refractive index heterogeneity in the fluid. The distortion also varies spatially and temporally, adding to the challenge. We propose a composite filter, the shadow-affected PIV region filter, which combines a series of conventional image filters to address this issue, focusing on optical distortion of thermal plumes in laminar flow. We verify the effectiveness of the filter using both synthetic particle images created from ray tracing and real particle images from the laboratory. For the first time, we effectively mitigate the optical distortion from plumes while preserving the in-plane plume velocity and overall flow pattern, with the PIV data alone. Our filter is efficient and does not require additional measurements, expensive ray tracing, or a large dataset to begin with. It can be extended to separate the flow field and the effect of optical distortion in other fluid experiments when the two components are visually distinct. Additionally, this filter can serve as a baseline algorithm for comparison when developing more advanced methods like neural networks.