A improved spectral reflectance reconstruction method is developed to transform camera RGB to spectral reflectance for skin images. Rather than using conventional direct or two-step processes, we transform camera RGB to skin reflectance directly using a principal component analysis (PCA) approach. The novelty in our direct method (RGB to spectra) is the use of a skin-specific colour characterisation chart with spectra closer to human skin spectra, and a new database of skin reflectances to derive the PCA bases. The experimental results using the facial images of 17 subjects demonstrate that our new direct method gives a significantly better performance than conventional, two-step methods and direct methods with traditional characterization charts. This new spectral reconstruction algorithm is sufficiently precise to reconstruct spectral properites relating to chromophores and its performance is within the acceptable range for maxillofacial soft tissue prostheses (error < 3 ΔE*_ab units).

A new CIE color appearance model (CIECAM02) has been developed. This paper describes the three major drawbacks of the earlier CIECAM97s model, and shows how the new model performs in these color regions. In addition, both models were tested using available data groups. The results are consistent in that CIECAM02 performed as well as, or better than, CIECAM97s in almost all cases, there being a large improvement in the prediction of saturation. The CIECAM02 model can therefore be considered as a possible replacement for CIECAM97s for all image applications.