Compressive light field photography using overcomplete dictionaries and optimized projections
Light field photography has gained a significant research interest in the last two decades; today, commercial light field cameras are widely available. Nevertheless, most existing acquisition approaches either multiplex a low-resolution light field into a single 2D sensor image or require multiple p...
| Hauptverfasser: | , , , |
|---|---|
| Weitere Verfasser: | |
| Format: | Artikel |
| Sprache: | en_US |
| Veröffentlicht: |
Association for Computing Machinery
2014
|
| Online Zugang: | http://hdl.handle.net/1721.1/92451 https://orcid.org/0000-0002-3254-3224 |
| Zusammenfassung: | Light field photography has gained a significant research interest in the last two decades; today, commercial light field cameras are widely available. Nevertheless, most existing acquisition approaches either multiplex a low-resolution light field into a single 2D sensor image or require multiple photographs to be taken for acquiring a high-resolution light field. We propose a compressive light field camera architecture that allows for higher-resolution light fields to be recovered than previously possible from a single image. The proposed architecture comprises three key components: light field atoms as a sparse representation of natural light fields, an optical design that allows for capturing optimized 2D light field projections, and robust sparse reconstruction methods to recover a 4D light field from a single coded 2D projection. In addition, we demonstrate a variety of other applications for light field atoms and sparse coding, including 4D light field compression and denoising. |
|---|