title: Compressive light field sensing.
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.
authors.affiliation: Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA. dbabacan@illinois.edu
authors.forename: S Derin
authors.initials: SD
authors.lastname: Babacan
authors.forename: Reto
authors.initials: R
authors.lastname: Ansorge
authors.forename: Martin
authors.initials: M
authors.lastname: Luessi
authors.forename: Pablo Ruiz
authors.initials: PR
authors.lastname: Matarán
authors.forename: Rafael
authors.initials: R
authors.lastname: Molina
authors.forename: Aggelos K
authors.initials: AK
authors.lastname: Katsaggelos