There is currently no standard method to map high-dimensional spectral data into a pseudocolor representation. A number of methods have bene developed for paraticular applications, but the results are often difficult to predict when the strategy is applied in other circumstances. A talented analyst can almost always create a color representation that highlights the specific feature of interest, but there is a need for a default strategy which can provide a reliable first look at the data in an unsupervised manner. In this paper, we introduce a principal components based mapping strategy that is built on the principles of human color vision. Orthogonal image information is mapped into orthogonal color processing channels, providing an ergonomic representation that more closely resembles scenes that human visual systems are trained to process. The specific transformation discussed in this paper is optimized for to the data set analyzed, but it provides a first step in the development of an invariant strategy for initial display of spectral data.
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