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arXiv · 2501.13334

Scalable dataset acquisition for data-driven lensless imaging

Clara S. Hung·Leyla A. Kabuli·Vasilisa Ponomarenko·Laura Waller
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Abstract

Data-driven developments in lensless imaging, such as machine learning-based reconstruction algorithms, require large datasets. In this work, we introduce a data acquisition pipeline that can capture from multiple lensless imaging systems in parallel, under the same imaging conditions, and paired with computational ground truth registration. We provide an open-access 25,000 image dataset with two lensless imagers, a reproducible hardware setup, and open-source camera synchronization code. Experimental datasets from our system can enable data-driven developments in lensless imaging, such as machine learning-based reconstruction algorithms and end-to-end system design.

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Clara S. Hung, Leyla A. Kabuli, Vasilisa Ponomarenko, Laura Waller. 2026-01-31. Scalable dataset acquisition for data-driven lensless imaging. https://doi.org/10.1117/12.3040992

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