NIR hyperspectral compressive imager based on a modified Fabry-Perot resonator

Yaniv Oiknine, Isaac August, Dan G. Blumberg, Adrian Stern

Research output: Contribution to journalArticlepeer-review

16 Scopus citations

Abstract

The acquisition of hyperspectral (HS) image datacubes with available 2D sensor arrays involves a time consuming scanning process. In the last decade, several compressive sensing (CS) techniques were proposed to reduce the HS acquisition time. In this paper, we present a method for near-infrared (NIR) HS imaging which relies on our rapid CS resonator spectroscopy technique. Within the framework of CS, and by using a modified Fabry-Perot resonator, a sequence of spectrally modulated images is used to recover NIR HS datacubes. Owing to the innovative CS design, we demonstrate the ability to reconstruct NIR HS images with hundreds of spectral bands from an order of magnitude fewer measurements, i.e. with a compression ratio of about 10:1. This high compression ratio, together with the high optical throughput of the system, facilitates fast acquisition of large HS datacubes.

Original languageEnglish
Article number044011
JournalJournal of Optics (United Kingdom)
Volume20
Issue number4
DOIs
StatePublished - 1 Apr 2018

Keywords

  • compressive sensing
  • computational imaging
  • hyperspectral
  • near-infrared

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Atomic and Molecular Physics, and Optics

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