Publications [#280504] of David J. Brady
- Hamza, AB; Brady, DJ, Reconstruction of reflectance spectra using robust nonnegative matrix factorization,
Ieee Transactions on Signal Processing, vol. 54 no. 9
pp. 3637-3642, Institute of Electrical and Electronics Engineers (IEEE), ISSN 1053-587X [TSP.2006.879282], [doi]
(last updated on 2019/11/14)
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.
Algorithms;Cost functions;Optimization;Principal component analysis;Spectroscopic analysis;Statistics;