A study of digital camera colorimetric characterization based on polynomial modeling

The digital camera is a powerful tool to capture images for rise in image p rocessing and colour communication. However, the RGB signals generated by a digital camera are device-dependent, i.e., different digital cameras produ ce different RGB responses for the same scene. Furthermore, they are not co lorimetric, i.e,, the output RGB signals no not directly correspond to the device-independent tristimulus values based on the CIE standard colorimetri c observer. One approach for deriving a colorimetric mapping between camera RGB signals and CIE tristimulus values uses polynomial modeling and is des cribed here. The least squares fitting technique was used to derive the coe fficients of 3 X n polynomial transfer matrices, yielding a modeling accura cy typically averaging 1 DeltaE units in CMC(I:II when a 3 X II matrix is u sed. Experiments were carried out to investigate the repeatability of the d igitizing system, characterization performance when different polynomials w ere used, modeling accuracy when 8-bit and 12-bit RGB data were used for ch aracterization, and the number of reference samples needed to achieve a rea sonable degree of modeling accuracy. Choice of characterization target and media and their effect on metamerism have been examined. It is demonstrated that a model is dependent upon both media and colorant, and applying a mod el to other media/colorants can lead to serious eye-camera metamerism probl ems. (C) 2001 John Wiley & Sons, Inc.