Predicting a surface color under different lights is an easy task if the surface reflectance function is available. However, often only colorimetric information is available, and the tristimulus values of a color that undergoes an illuminant change are estimated using transforms inspired by the von Kries coefficient rule model. We propose a new method, based on the reconstruction of multispectral data, for modeling illuminant change. It assumes that the problem is specific for a domain of colors, and that this domain can be modeled in a three dimensional Gaussian space. The performance of our method is compared with that of the simple von Kries diagonal transform, and the results are reported for three sets of data
Zuffi, S., Schettini, R. (2005). Using recovered reflectance to predict color. In Color imaging X : processing, hardcopy, and applications : 17-20 January 2005, San Jose, California, USA (pp.47-52). SPIE-INT SOC OPTICAL ENGINEERING [10.1117/12.586946].
Using recovered reflectance to predict color
Schettini, R
2005
Abstract
Predicting a surface color under different lights is an easy task if the surface reflectance function is available. However, often only colorimetric information is available, and the tristimulus values of a color that undergoes an illuminant change are estimated using transforms inspired by the von Kries coefficient rule model. We propose a new method, based on the reconstruction of multispectral data, for modeling illuminant change. It assumes that the problem is specific for a domain of colors, and that this domain can be modeled in a three dimensional Gaussian space. The performance of our method is compared with that of the simple von Kries diagonal transform, and the results are reported for three sets of data
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
