Journal
ACM TRANSACTIONS ON GRAPHICS
Volume 32, Issue 4, Pages -Publisher
ASSOC COMPUTING MACHINERY
DOI: 10.1145/2461912.2461914
Keywords
computational photography; compressive sensing
Categories
Funding
- NSERC
- DARPA SCENICC program
- Alfred P. Sloan Research Fellowship
- DARPA Young Faculty Award
- Direct For Computer & Info Scie & Enginr
- Div Of Information & Intelligent Systems [1218411] Funding Source: National Science Foundation
- Div Of Information & Intelligent Systems
- Direct For Computer & Info Scie & Enginr [1116452] Funding Source: National Science Foundation
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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.
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