Papers Published

1. Hamza, A. Ben and Brady, David J., Reconstruction of reflectance spectra using robust nonnegative matrix factorization, IEEE Transactions on Signal Processing, vol. 54 no. 9 (2006), pp. 3637 - 3642 [TSP.2006.879282] .
   (last updated on 2007/04/11)

   Abstract:
   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.

   Keywords:
   Algorithms;Cost functions;Optimization;Principal component analysis;Spectroscopic analysis;Statistics;