Subspace Structure Regularized Nonnegative Matrix Factorization for Hyperspectral Unmixing

Zhou, L., Zhang, X., Wang, J. et al. (5 more authors) (2020) Subspace Structure Regularized Nonnegative Matrix Factorization for Hyperspectral Unmixing. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. ISSN 2151-1535

Abstract

Metadata

Authors/Creators:
Copyright, Publisher and Additional Information: This is an author-produced version of the published paper. Uploaded in accordance with the publisher’s self-archiving policy. Further copying may not be permitted; contact the publisher for details.
Keywords: Hyperspectral imaging,Matrix decomposition,Sparse matrices,Graphical models,Distribution functions,Robustness,Hyperspectral unmixing,linear mixing model (LMM),nonnegative matrix factorization (NMF),subspace structure,similar graph
Dates:
  • Published (online): 22 July 2020
Institution: The University of York
Academic Units: The University of York > Faculty of Sciences (York) > Computer Science (York)
Depositing User: Pure (York)
Date Deposited: 24 Jul 2020 08:50
Last Modified: 07 Sep 2022 13:56
Published Version: https://doi.org/10.1109/JSTARS.2020.3011257
Status: Published online
Refereed: Yes
Identification Number: https://doi.org/10.1109/JSTARS.2020.3011257

Download

Filename: 09146211.pdf

Description: Subspace Structure Regularized Nonnegative Matrix Factorization for Hyperspectral Unmixing

Share / Export

Statistics