|Title||Reconstruction of reflectance spectra using robust nonnegative matrix factorization|
|Publication Type||Journal Article|
|Year of Publication||2006|
|Authors||AB Hamza, and DJ Brady|
|Journal||Ieee Transactions on Signal Processing|
|Pagination||3637 - 3642|
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 Title||Ieee Transactions on Signal Processing|