Abstract
The wavelet packet transform is studied as a tool for improving pattern recognition based on near-infrared spectra. Application to the preprocessing of the spectra improves the classification when compared to using either the standard normal variate method or no pretreatment at all. Selecting features from a local discriminant basis instead of from a full decomposition does not improve the results.
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