Chemical Image files are typically immense; for example,
a hypercube with spatial dimensions of 256 · 256 pixels
operating at 150 wavebands contains more than 65,000
spectra, each with 150 data points. In attempting to extract
useful information from such information-dense datasets a
multidisciplinary approach is required, involving advanced
image processing and multivariate statistical methods.
Numerous techniques exist to mine the chemical, physical
and spatial information hidden in Chemical Images. The
challenge is to reduce the dimensionality of the data while
retaining important spectral information with the power to
classify important areas of a sample effectively. Typical
steps involved in analysing Chemical Images are outlined
in Fig. 3 and described below.