Particle depth position detection by 2D correlation in digital in-line holography

Area of Science:

• Fluid dynamics
• Optical metrology
• Digital holography

Background:

• Hologram truncation is a significant challenge in digital holographic particle image velocimetry (DH-PIV).
• Truncation causes particle images to deform when particle projections are near the sensor edge.
• Existing particle detection algorithms struggle with these deformations.

Purpose of the Study:

• To address the challenge of hologram truncation in DH-PIV.
• To refine an existing particle position detection algorithm for deformed images.
• To improve the accuracy of particle position detection in DH-PIV.

Main Methods:

• Utilized the convolution approach for hologram reconstruction.
• Adapted and refined a particle detection algorithm originally for analog holography.
• Validated the refined algorithm using numerical simulations and experimental data.

Main Results:

• Demonstrated that hologram truncation leads to deformed particle images.
• Showcased the improved performance of the refined algorithm in detecting particle positions from deformed images.
• Confirmed the algorithm's effectiveness through both numerical and experimental validation.

Conclusions:

• The refined algorithm effectively detects particle positions from truncated holograms in DH-PIV.
• This advancement enhances the reliability and accuracy of DH-PIV measurements in challenging conditions.
• The study provides a practical solution for a prominent issue in holographic velocimetry.