Reconstruction of reflectance spectra using robust nonnegative matrix factorization

Published

Journal Article

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.

Full Text

Duke Authors

Cited Authors

  • Hamza, AB; Brady, DJ

Published Date

  • September 1, 2006

Published In

Volume / Issue

  • 54 / 9

Start / End Page

  • 3637 - 3642

International Standard Serial Number (ISSN)

  • 1053-587X

Digital Object Identifier (DOI)

  • 10.1109/TSP.2006.879282

Citation Source

  • Scopus