Scalable dataset acquisition for data-driven lensless imaging
Fuente:
arXiv
Guardado en:
| Autores principales: | , , , |
|---|---|
| Formato: | Preprint |
| Publicado: |
2025
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
| _version_ | 1866910006902784000 |
|---|---|
| author | Hung, Clara S. Kabuli, Leyla A. Ponomarenko, Vasilisa Waller, Laura |
| author_facet | Hung, Clara S. Kabuli, Leyla A. Ponomarenko, Vasilisa Waller, Laura |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2501_13334 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Scalable dataset acquisition for data-driven lensless imaging Hung, Clara S. Kabuli, Leyla A. Ponomarenko, Vasilisa Waller, Laura Image and Video Processing Optics 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. |
| title | Scalable dataset acquisition for data-driven lensless imaging |
| topic | Image and Video Processing Optics |
| url | https://arxiv.org/abs/2501.13334 |