Self-calibrated and SNR-enhanced particle holography

Area of Science:

• Optics and Photonics
• Particle Imaging Velocimetry
• Digital Holography

Background:

• In-line particle holography is susceptible to speckle noise, degrading reconstruction quality.
• Current methods to reduce noise often rely on post-processing algorithms or require intensive system calibration.
• Accurate knowledge of illumination angles is critical for high-fidelity holographic reconstruction.

Purpose of the Study:

• To develop a self-calibrated approach for in-line particle holography that eliminates the need for time- and labor-intensive pre-calibration.
• To estimate illumination angles directly from experimentally collected holograms.
• To improve the signal-to-noise ratio (SNR) and mitigate speckle noise without additional hardware.

Main Methods:

• A novel self-calibrated method is proposed to estimate illumination angles directly from recorded holograms.
• The approach leverages multiple holograms captured under varying illumination angles.
• No additional hardware or specific calibration images are required.

Main Results:

• The proposed method successfully estimates illumination angles, correcting for misalignment.
• Demonstrated effectiveness in both numerical simulations and experimental data.
• The self-calibration approach enhances SNR and reduces speckle noise in reconstructed images.

Conclusions:

• The developed self-calibrated technique offers an efficient and accurate solution for illumination angle estimation in in-line particle holography.
• This method significantly reduces the burden of system calibration, making holographic particle imaging more accessible.
• The findings pave the way for improved quality and reliability in holographic particle analysis.