Enhancing Pure-Pixel Identification Performance via Preconditioning

DOI10.1137/140994915zbMath1325.65083arXiv1406.5286OpenAlexW3099035708MaRDI QIDQ3192648

Wing-Kin Ma, Nicolas Gillis

Publication date: 13 October 2015

Published in: SIAM Journal on Imaging Sciences (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1406.5286

zbMATH Keywords

semidefinite programmingpreconditioningrobustness to noisesuccessive projection algorithmhyperspectral unmixingprewhiteningnear-separable nonnegative matrix factorizationpure-pixel search

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Semidefinite programming (90C22) Methods of successive quadratic programming type (90C55) Preconditioners for iterative methods (65F08)

Related Items

Efficient preconditioning for noisy separable nonnegative matrix factorization problems by successive projection based low-rank approximations, Enhancing Pure-Pixel Identification Performance via Preconditioning, Robustness analysis of preconditioned successive projection algorithm for general form of separable NMF problem

Uses Software

• CVX

Cites Work

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