Colorimetric modeling for vision systems

A colorimetric modeling technique is proposed to give a computational model associated with colorimetry so that the repre- sentation of color acquired from camera imaging is accurate and meaningful. First of all, the camera spectral responses are esti- mated and the colorimetric quality is evaluated to reveal the feasi- bility of this work. In the modeling process, we present a spectral matching method and an approach of determining a reference-white luminance. As a result, the acquired color and the true (or mea- sured) color can be well coordinated, with the strength of a global illumination or display white, in a perceptually uniform color space, e.g., in CIE 1976 L*a*b* space (abbreviated as CIELAB). Then, lower-degree polynomial regression is employed to eliminate color errors due to the mismatch between spectral response functions. Experimental results indicate that the root-mean-square DEab value (i.e., color error) from the degree-3 polynomial regression is less than a just-noticeable difference (about 2.3) in CIELAB. It appears that the proposed technique can establish an accurate colorimetric model for vision systems. © 2000 SPIE and IS&T. (S1017-9909(00)01604-4)