In this talk we will discuss calibration transforms that map the XYZ values generated by the same surface under different illuminants. We use the phrase calibration transforms to distinguish between analyses based on the physical properties of surfaces and illuminants, and to
distinguish them from appearance transforms based on measurements of color appearance. Calibration transforms describe how the XYZ coordinates measured for a surface change with illumination. Appearance transforms describe how the XYZ coordinates of a particular appearance change
with illumination. The change in XYZ values due to calibration and appearance transforms do not generally coincide.Calibration and appearance transforms serve different and useful functions in color management systems. Calibration transforms can be used to correct the device-independent
color descriptors of surfaces that have been calibrated for one illuminant but will be rendered under a different illuminant. These calculations play an important role in device calibration. Appearance transforms share a similar computational structure, but they have a different goal and are
not XYZ matches.One step in performing automated calibration transforms is to estimate the illuminant spectral power distribution (SPD). Performing the transform is much simpler if one can estimate the illuminant SPD from a three-sensor device, rather than using a spectroradiometer.
We first analyze an illuminant estimation method based on using linear models of the illuminant SPD. This solution is taken from the color constancy literature and assumes very little or no information about the objects in the image.In many practical applications the need for accurate
calibration transforms outweighs the advantages of algorithms based on little or no information about the surfaces and illuminants in a scene. In this paper we describe how a measurement of a single calibration with known surface target, such as the Macbeth Color-Checker, improves our ability
to estimate the illuminant SPD. This method may be useful in practical applications where a single calibration measurement is permitted.
Journal Title : Color and Imaging Conference
Publisher Name : Society of Imaging Science and Technology
Publisher Location : 7003 Kilworth Lane, Springfield, VA 22151, USA
In this talk we will discuss calibration transforms that map the XYZ values generated by the same surface under different illuminants. We use the phrase calibration transforms to distinguish between analyses based on the physical properties of surfaces and illuminants, and to
distinguish them from appearance transforms based on measurements of color appearance. Calibration transforms describe how the XYZ coordinates measured for a surface change with illumination. Appearance transforms describe how the XYZ coordinates of a particular appearance change
with illumination. The change in XYZ values due to calibration and appearance transforms do not generally coincide.Calibration and appearance transforms serve different and useful functions in color management systems. Calibration transforms can be used to correct the device-independent
color descriptors of surfaces that have been calibrated for one illuminant but will be rendered under a different illuminant. These calculations play an important role in device calibration. Appearance transforms share a similar computational structure, but they have a different goal and are
not XYZ matches.One step in performing automated calibration transforms is to estimate the illuminant spectral power distribution (SPD). Performing the transform is much simpler if one can estimate the illuminant SPD from a three-sensor device, rather than using a spectroradiometer.
We first analyze an illuminant estimation method based on using linear models of the illuminant SPD. This solution is taken from the color constancy literature and assumes very little or no information about the objects in the image.In many practical applications the need for accurate
calibration transforms outweighs the advantages of algorithms based on little or no information about the surfaces and illuminants in a scene. In this paper we describe how a measurement of a single calibration with known surface target, such as the Macbeth Color-Checker, improves our ability
to estimate the illuminant SPD. This method may be useful in practical applications where a single calibration measurement is permitted.