The aim of the study is to reconstruct spectral and colorimetric data, using trichromatic and multi-channel imaging. An experimental image acquisition system is used, which besides trichromatic RGB filters also provides the possibility of acquiring multi-channel images, using 7 narrowband filters. To derive mappings to colorimetric and multispectral representations, two conceptually different approaches are used. In the model-based approach, the physical model describing the image acquisition process is inverted, to reconstruct spectral reflectance from the recorded device response. A priori knowledge on the smooth nature of spectral reflectances is utilized, by representing the reconstructed spectra as linear combinations of basis functions, using Fourier basis and a database of real reflectance spectra. In the empirical approach, the characteristics of the individual components are ignored, and the functions are derived by relating the device response for a set of training colors to the corresponding colorimetric and spectral measurements. Beside colorimetric regression, mapping device values directly to CIEXYZ and CIELAB, experiments are also made on reconstructing spectral reflectance, using least squares regression techniques.

The results indicate that for trichromatic imaging, accurate colorimetric mappings can be derived by the empirical approach, using polynomial regression to CIEXYZ and CIELAB. Because of the media-dependency, the characterization functions must be derived for each combination of media and colorants. However, accurate spectral reconstructions require for multi-channel imaging, using model-based device characterization. Moreover, the model-based approach is general, since it is based on the spectral characteristics of the image acquisition system, rather than the characteristics of a set of color samples.