spectral reflectance can be considered as vector spaces of the imaging pixels and can be analyzed by the PCA method into several eigenvectors. The principal components are the linear combinations of the eigenvectors.11 , 12 The resulting components are the vectors representing the primary spectral reflectance curves of the image. The primary colour of the blue-and-white porcelain can then be derived from the first component of the PCA analysis, not just simply from averaging of the sampled spectral data. Physically, the different intensities of the blue colour material (cobalt oxide) on the porcelain correspond to different amounts of the principal component, and consequently the primary colour of each blue-and-white porcelain can be derived. The spectral distribution of different blue-and-white wares can be compared, and consequently the hue angle can be computed to distinguish the numerical difference of the material itself and