# Hybrid Iterating-Averaging Low Photon Budget Gabor Holographic Microscopy

## TL;DR

This paper introduces a new algorithm for low-light microscopy that improves image quality and reduces cell damage during long-term observations.

## Contribution

The novel IGA algorithm combines iterative phase retrieval with frame averaging to suppress noise and twin image artifacts in low-photon holographic imaging.

## Key findings

- IGA outperforms conventional methods in reconstructing phase images under high-noise conditions.
- Experimental validation confirmed IGA's efficacy in high-speed imaging of dynamic biological samples.
- IGA works well for optically thin samples with low signal-to-noise ratios.

## Abstract

Achieving high-contrast,
label-free imaging with minimal impact
on live cell culture behavior remains a primary challenge in quantitative
phase imaging (QPI). By enabling imaging under low illumination intensities
(low photon budget, LPB), it is possible to minimize cell photostimulation,
phototoxicity, and photodamage while supporting long-term and high-speed
observations. However, LPB imaging introduces significant difficulties
in QPI due to high levels of camera shot noise and quantification
noise. Digital in-line holographic microscopy (DIHM) is a QPI technique
known for its robustness against LPB data. However, simultaneous minimization
of shot noise and inherent in DIHM twin image perturbation remains
a critical challenge. In this study, we present the iterative Gabor
averaging (IGA) algorithm, a novel approach that integrates iterative
phase retrieval with frame averaging to effectively suppress both
twin image disturbance and shot noise in multiframe DIHM. The IGA
algorithm achieves this by leveraging an iterative process that reconstructs
high-fidelity phase images while selectively averaging camera shot
noise across frames. Our simulations demonstrate that IGA consistently
outperforms conventional methods, achieving superior reconstruction
accuracy, particularly under high-noise conditions. Experimental validations
involving high-speed imaging of dynamic sperm cells and a static phase
test target measurement under low illumination further confirmed IGA’s
efficacy. The algorithm also proved successful for optically thin
samples, which often yield low signal-to-noise holograms even at high
photon budgets. These advancements make IGA a powerful tool for photostimulation-free,
high-speed imaging of dynamic biological samples and enhance the ability
to image samples with extremely low optical thickness, potentially
transforming biomedical and environmental applications in low-light
settings.