On the Particle Image Overlap in Single Camera Defocusing Approaches

TL;DR

This paper develops a statistical model to quantify particle image overlap in single-camera defocusing techniques, providing practical guidelines to optimize experimental parameters for more accurate particle tracking and sizing.

Contribution

It introduces a universal model for particle image overlap based on seeding density, validated with experimental data, aiding in experimental design and measurement accuracy in DPTV and IPI.

Findings

Seeding density is a key universal scaling parameter for PI overlap.

Critical threshold at seeding density 0.25 where each particle, on average, overlaps with one other.

The model accurately predicts overlap metrics even with non-uniform particle sizes and mild astigmatism.

Abstract

Particle image (PI) overlap presents a significant challenge in single-camera particle tracking and sizing techniques such as Defocusing Particle Tracking Velocimetry (DPTV) and Interferometric Particle Imaging (IPI). In DPTV, overlap obscures PI boundaries, complicating the detection and accurate estimation of PI diameter and center position, which increases uncertainty in the reconstructed particle positions. In IPI, overlap reduces the usable area of the interference pattern, limiting the accuracy of particle size determination. This study introduces a statistical model to quantify PI overlap independently from the optical setup, source density, or PI size. The model assumes uniformly distributed, uniformly sized circular PIs and is validated against experimental data featuring non-uniform sizes and mild astigmatism (up to aspect ratios of 1.66), demonstrating strong agreement. The present study reveals that the seeding density $\mathcal{S}$ serves as a strong universal scaling parameter for PI overlap. Key overlap metrics, including the number of overlaps per PI, the fraction of overlap-free PIs, and the usable PI area are analyzed as functions of the seeding density $\mathcal{S}$. The results reveal a critical threshold at $\mathcal{S} = 0.25$, where each PI experiences, on average, one overlap. The study provides practical guidance for experimental design by linking overlap metrics to controllable parameters such as source density, defocus length, and aperture diameter. The presented models serve as lookup tools to help experimenters maintain PI overlap within acceptable limits, enabling more reliable and quantitatively robust measurements in DPTV and IPI applications.