On plenoptic multiplexing and reconstruction

Gordon Wetzstein*, Ivo Ihrke, Wolfgang Heidrich

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

34 Scopus citations

Abstract

Photography has been striving to capture an ever increasing amount of visual information in a single image. Digital sensors, however, are limited to recording a small subset of the desired information at each pixel. A common approach to overcoming the limitations of sensing hardware is the optical multiplexing of high-dimensional data into a photograph. While this is a well-studied topic for imaging with color filter arrays, we develop a mathematical framework that generalizes multiplexed imaging to all dimensions of the plenoptic function. This framework unifies a wide variety of existing approaches to analyze and reconstruct multiplexed data in either the spatial or the frequency domain. We demonstrate many practical applications of our framework including high-quality light field reconstruction, the first comparative noise analysis of light field attenuation masks, and an analysis of aliasing in multiplexing applications.

Original languageEnglish (US)
Pages (from-to)384-400
Number of pages17
JournalInternational Journal of Computer Vision
Volume101
Issue number2
DOIs
StatePublished - Jan 2013

Keywords

  • Computational photography
  • Light fields
  • Optical multiplexing
  • Plenoptic function

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence

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