Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 398

The DOI matches its Crossref record; 30 of the 30 references it cites were found in a registry or an index.

Compressive light field photography using overcomplete dictionaries and optimized projections

Open access
Marwah, Kshitij, Wetzstein, Gordon, Bando, Yosuke, Raskar, Ramesh·2013·ACM Transactions on Graphics

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.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1145/2461912.2461914

Cites

30 of 30 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 30 references

Cited by

See all 398

Metadata

Authors
Marwah, K., Wetzstein, G., Bando, Y., & Raskar, R.
Venue
ACM Transactions on Graphics
Published
2013-07-21
Volume
32
Issue
4
Pages
1-12
ISSN
  • 0730-0301 (ISSN-L)
  • 1557-7368
OpenAlex
W2119967924
Cited by
398
References
30
FWCI
33.07
Type
journal article
Language
en
Open access
green

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Compressive light field photography using overcomplete dictionaries and optimized projections. https://app.cochat.ai/papers/10.1145/2461912.2461914
The paper
Marwah, K., Wetzstein, G., Bando, Y., & Raskar, R. (2013). Compressive light field photography using overcomplete dictionaries and optimized projections. ACM Transactions on Graphics. https://doi.org/10.1145/2461912.2461914

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.