Compressive light field sensing

S. Derin Babacan*, Reto Ansorge, Martin Luessi, Pablo Ruiz Mataran, Rafael Molina, Aggelos K. Katsaggelos

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

67 Scopus citations

Abstract

We propose a novel design for light field image acquisition based on compressive sensing principles. By placing a randomly coded mask at the aperture of a camera, incoherent measurements of the light passing through different parts of the lens are encoded in the captured images. Each captured image is a random linear combination of different angular views of a scene. The encoded images are then used to recover the original light field image via a novel Bayesian reconstruction algorithm. Using the principles of compressive sensing, we show that light field images with a large number of angular views can be recovered from only a few acquisitions. Moreover, the proposed acquisition and recovery method provides light field images with high spatial resolution and signal-to-noise-ratio, and therefore is not affected by limitations common to existing light field camera designs. We present a prototype camera design based on the proposed framework by modifying a regular digital camera. Finally, we demonstrate the effectiveness of the proposed system using experimental results with both synthetic and real images.

Original languageEnglish (US)
Article number6248701
Pages (from-to)4746-4757
Number of pages12
JournalIEEE Transactions on Image Processing
Volume21
Issue number12
DOIs
StatePublished - 2012

Keywords

  • Bayesian methods
  • coded aperture
  • compressive sensing
  • computational photography
  • image reconstruction
  • light fields

ASJC Scopus subject areas

  • Software
  • Computer Graphics and Computer-Aided Design

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