Reconstruction algorithms for compressive hyperspectral imaging systems with separable spatial and spectral operators

Yaniv Oiknine, Yitzhak August, Adrian Stern

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Scopus citations

Abstract

Recently we introduced a hyperspectral compressive sensing scheme that uses separable projections in the spatial and spectral domains. The separable encoding schemes facilitates the optical implementation, reduces the computational burden dramatically, and storage requirements. Owing to these benefits we have been able to encode the hyperspectral cube in all three dimensions. In this work we present a comparison between various reconstructions methods applied to the hyperspectral data captured with our separable compressive sensing systems.

Original languageEnglish
Title of host publicationApplications of Digital Image Processing XXXVII
EditorsAndrew G. Tescher
PublisherSPIE
ISBN (Electronic)9781628412444
DOIs
StatePublished - 1 Jan 2014
EventApplications of Digital Image Processing XXXVII - San Diego, United States
Duration: 18 Aug 201421 Aug 2014

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume9217
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Conference

ConferenceApplications of Digital Image Processing XXXVII
Country/TerritoryUnited States
CitySan Diego
Period18/08/1421/08/14

Keywords

  • Compressed sensing
  • Hyperspectral imaging
  • Separable operators
  • Spectroscopy

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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