Skip to main content
Article thumbnail
Location of Repository

Compressive-ProjectionPrincipalComponent Analysis forthe Compression ofHyperspectralSignatures JamesE.Fowler

By 

Abstract

A method is proposed for the compression of hyperspectral signature vectors on severely resourceconstrainedencodingplatforms. Theproposedtechnique,compressive-projectionprincipalcomponentanalysis,recoversfromrandomprojectionsnotonlytransformcoefficientsbutalsoanapproximationtotheprincipal-componentbasis,effectivelyshiftingthecomputationalburdenofprincipal componentanalysisfromtheencodertothedecoder. Initsuseofrandomprojections,theproposed methodresemblescompressedsensingbutdiffersinthatsimplelinearreconstructionsufficesforcoefficient recovery. Existing results from perturbation theory are invoked to argue for the robustness under quantization of the eigenvector-recovery process central to the proposed technique, and experimentalresultsdemonstrateasignificantrate-distortionperformanceadvantageovercompressed sensingusingavarietyof popular bases

Year: 2013
OAI identifier: oai:CiteSeerX.psu:10.1.1.308.3190
Provided by: CiteSeerX
Download PDF:
Sorry, we are unable to provide the full text but you may find it at the following location(s):
  • http://citeseerx.ist.psu.edu/v... (external link)
  • http://www.ece.msstate.edu/~fo... (external link)
  • Suggested articles


    To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.