Compressive light field photography using overcomplete dictionaries and optimized projections
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No Canadian affiliation. An affiliation-only frame — the usual design — would never have seen this work. It is one of the works that make the case for inverting the frame.
Machine scores (provisional)
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- Teacher spread
- 0.247 · how far apart the two teachers sit on this one work
- Validation status
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Abstract
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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The record
- Venue
- ACM Transactions on Graphics
- Topic
- Advanced Vision and Imaging
- Field
- Computer Science
- Canadian institutions
- —
- Funders
- Natural Sciences and Engineering Research Council of CanadaDefense Advanced Research Projects AgencyAlfred P. Sloan Foundation
- Keywords
- Light fieldComputer visionComputer scienceComputational photographyArtificial intelligenceField (mathematics)PhotographyProjection (relational algebra)Compressed sensingOpticsComputer graphics (images)Image processingImage (mathematics)PhysicsAlgorithmMathematics
- Has abstract in OpenAlex
- yes