Photon counting compressive depth mapping

Gregory A. Howland, Daniel J. Lum, Matthew R. Ware, John C. Howell

Research output: Contribution to journalArticlepeer-review

158 Scopus citations

Abstract

We demonstrate a compressed sensing, photon counting lidar system based on the single-pixel camera. Our technique recovers both depth and intensity maps from a single under-sampled set of incoherent, linear projections of a scene of interest at ultra-low light levels around 0:5 picowatts. Only two-dimensional reconstructions are required to image a three-dimensional scene. We demonstrate intensity imaging and depth mapping at 256-256 pixel transverse resolution with acquisition times as short as 3 seconds. We also show novelty filtering, reconstructing only the difference between two instances of a scene. Finally, we acquire 32-32 pixel real-time video for three-dimensional object tracking at 14 frames-per-second.

Original languageAmerican English
Pages (from-to)23822-23837
Number of pages16
JournalOptics Express
Volume21
Issue number20
DOIs
StatePublished - 7 Oct 2013
Externally publishedYes

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