Abstract
A calibration transfer method for near-infrared (NIR) spectra based on spectral regression is proposed. Spectral regression method can reveal low dimensional manifold structure in high dimensional spectroscopic data and is suitable to transfer the NIR spectra of different instruments. A comparative study of the proposed method and piecewise direct standardization (PDS) for standardization on two benchmark NIR data sets is presented. Experimental results show that spectral regression method outperforms PDS and is quite competitive with PDS with background correction. When the standardization subset has sufficient samples, spectral regression method exhibits excellent performance.
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