This study reports on the application of Raman and near-infrared (NIR) imaging techniques for determining the spatial distribution of all (five) components in a common type of pharmaceutical tablet manufactured in two different ways. Multivariate chemical images were produced as principal component (PC) scores, while univariate images were produced by using the most unique spectra selected by the orthogonal projection approach (OPA), a searching algorithm. Multivariate Raman images were obtained for all five components in both tablets, while only two or three components could be imaged with the NIR instrument. Very interesting PC results are reported that in effect cast doubt on the effectiveness of the established criteria for determining signal-related PCs in the Raman data. PCA has been found to be indispensable for imaging the minor components using the Raman data. Significant similarity between the multivariate and univariate chemical images has been noted despite there being considerable spectral overlap within the Raman and, especially, within the NIR mapping data sets. Gray-scale images are carefully thresholded, which allowed for quantitative comparison of the obtained binarized images. A thorough discussion is given on the problems and approximations needed for producing composite images.