Reconstruction of reflectance spectra using robust nonnegative matrix factorization
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| Authors | A. Hamza, D. Brady |
| Journal/Conference Name | I |
| Paper Category | Signal Processing |
| Paper 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 |
| Date of publication | 2006 |
| Code Programming Language | HTML |
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