Scalable dataset acquisition for data-driven lensless imaging

2025/01/23 by Hung, Clara S., Kabuli, Leyla A., Ponomarenko, Vasilisa +1 · 1 citation
#FOS: Electrical engineering #FOS: Physical sciences #Image and Video Processing (eess.IV) #Optics (physics.optics) #electronic engineering #information engineering

paper · doi:10.48550/arxiv.2501.13334

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.

Cited by

• Designing lensless imaging systems to maximize information capture

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