Optimized sampling for view interpolation in light fields using local Dictionaries

David C. Schedl, Clemens Birklbauer, Oliver Bimber

Research output: Chapter in Book/Report/Conference proceedingsConference contributionpeer-review

Abstract

We present an angular superresolution method for light fields captured with a sparse camera array. Our method uses local dictionaries extracted from a sampling mask for upsampling a sparse light field to a dense light field by applying compressed sensing reconstruction. We derive optimal sampling masks by minimizing the coherence for representative global dictionaries. The desired output perspectives and the number of available cameras can be arbitrarily specified. We show that our method yields qualitative improvements compared to previous techniques.

Original languageEnglish
Title of host publicationACM SIGGRAPH 2017 Posters, SIGGRAPH 2017
PublisherAssociation for Computing Machinery, Inc
ISBN (Electronic)9781450350150
DOIs
Publication statusPublished - 30 Jul 2017
Externally publishedYes
Event44th International Conference on Computer Graphics and Interactive Techniques, ACM SIGGRAPH 2017 - Los Angeles, United States
Duration: 30 Jul 20173 Aug 2017

Publication series

NameACM SIGGRAPH 2017 Posters, SIGGRAPH 2017

Conference

Conference44th International Conference on Computer Graphics and Interactive Techniques, ACM SIGGRAPH 2017
Country/TerritoryUnited States
CityLos Angeles
Period30.07.201703.08.2017

Keywords

  • Compressed sensing
  • Computational photography
  • Light fields
  • Up sampling
  • View interpolation

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