Sparsity and structure in hyperspectral imaging: Sensing, reconstruction, and target detection

Rebecca M. Willett, Marco F. Duarte, Mark A. Davenport, Richard G. Baraniuk

Research output: Contribution to journalArticlepeer-review

155 Scopus citations

Abstract

Hyperspectral imaging is a powerful technology for remotely inferring the material properties of the objects in a scene of interest. Hyperspectral images consist of spatial maps of light intensity variation across a large number of spectral bands or wavelengths; alternatively, they can be thought of as a measurement of the spectrum of light transmitted or reflected from each spatial location in a scene. Because chemical elements have unique spectral signatures, observing the spectra at a high spatial and spectral resolution provides information about the material properties of the scene with much more accuracy than is possible with conventional three-color images. As a result, hyperspectral imaging is used in a variety of important applications, including remote sensing, astronomical imaging, and fluorescence microscopy.

Original languageEnglish (US)
Article number6678233
Pages (from-to)116-126
Number of pages11
JournalIEEE Signal Processing Magazine
Volume31
Issue number1
DOIs
StatePublished - Jan 2014

ASJC Scopus subject areas

  • Signal Processing
  • Electrical and Electronic Engineering
  • Applied Mathematics

Fingerprint

Dive into the research topics of 'Sparsity and structure in hyperspectral imaging: Sensing, reconstruction, and target detection'. Together they form a unique fingerprint.

Cite this