Reconstruction of reflectance spectra using robust nonnegative matrix factorization

TitleReconstruction of reflectance spectra using robust nonnegative matrix factorization
Publication TypeJournal Article
Year of Publication2006
AuthorsAB Hamza, and DJ Brady
JournalIeee Transactions on Signal Processing
Start Page3637
Pagination3637 - 3642
Date Published09/2006

In this correspondence, we present a robust statistics-based nonnegative matrix factorization (RNMF) approach to recover the measurements in reflectance spectroscopy. The proposed algorithm is based on the minimization of a robust cost function and yields two equations updated alternatively. Unlike other linear representations, such as principal component analysis, the RNMF technique is resistant to outliers and generates nonnegative-basis functions, which balance the logical attractiveness of measurement functions against their physical feasibility. Experimental results on a spectral library of reflectance spectra are presented to illustrate the much improved performance of the RNMF approach. © 2006 IEEE.

Short TitleIeee Transactions on Signal Processing