Performance analysis of unsupervised unmixing models for thermal hyepsrpectral

Michal Shimoni, Xavier Briottet, Manuel Cubero-Castan, Christiaan Perneel, Véronique Achard, Jocelyn Chanussot

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

Abstract

Hyperspectral unmixing which consists of decomposing the measured pixel radiance into mixtures of 'pure' spectra whose fractions are referred to as abundances, is a common procedure in the signal and image applications. In this paper, the performance of unsupervised unmixing methods for hyperspectral data is evaluated using airborne thermal data and pixel-based ground truth in-situ. Specifically, the procedures of endmember extraction and mixing using linear and bilinear models are validated using set of pixels whose mixing proportion are known.

Original languageEnglish
Title of host publication2012 4th Workshop on Hyperspectral Image and Signal Processing, WHISPERS 2012
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Print)9781479934065
DOIs
Publication statusPublished - 2012
Event2012 4th Workshop on Hyperspectral Image and Signal Processing, WHISPERS 2012 - Shanghai, China
Duration: 4 Jun 20127 Jun 2012

Publication series

NameWorkshop on Hyperspectral Image and Signal Processing, Evolution in Remote Sensing
ISSN (Print)2158-6276

Conference

Conference2012 4th Workshop on Hyperspectral Image and Signal Processing, WHISPERS 2012
Country/TerritoryChina
CityShanghai
Period4/06/127/06/12

Keywords

  • bilinear model
  • endmembers
  • hyperspectral images
  • linear model
  • spectral unmixing

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