Hybrid Iterating-Averaging Low Photon Budget Gabor Holographic Microscopy

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.