Mark D Fairchild1. 1. Munsell Color Science Laboratory, Chester F. Carlson Center for Imaging Science, Rochester Institute of Technology, Rochester, NY 14623-5604, USA. mdf@cis.rit.edu
Abstract
OBJECTIVES: Teeth in a patient's mouth in a dental office, or in the natural environment, represent very complex stimuli for the human color vision system. Predicting their perceived color is a daunting task at best. Colorimetry is designed mainly for the evaluation of uniform, flat, opaque, materials of fairly large size viewed on a medium-grey background under near-daylight sources of fairly high luminance. On the contrary, in situ teeth vary spatially, are curved and ridged, translucent, relatively small, and viewed against a variable background under nonuniform, and typically nonstandard, illumination. These differences in stimuli and viewing conditions summarize the difficulty in predicting the color appearance of teeth. SOURCES: The field of color science has extended basic colorimetry, as represented by CIE XYZ and CIELAB coordinates, to more complex visual stimuli and viewing environments. The CIECAM02 color appearance model accurately addresses issues of chromatic adaptation, luminance effects and adaptation, background and surround effects, and the higher dimensionality of color appearance. Such models represent a significant advance and are used successfully in a variety of applications. However, many stimuli vary in space and time at scales not addressed by typical color appearance models. For example, high-definition video images would fall into such a category and so would in situ human teeth. More recently, color appearance models and image quality metrics have been combined to create image appearance models for even more complex visual stimuli. CONCLUSIONS: This paper provides an overview of fundamental and advanced colorimetry leading up to color appearance and image appearance models and their potential application in dentistry.
OBJECTIVES: Teeth in a patient's mouth in a dental office, or in the natural environment, represent very complex stimuli for the human color vision system. Predicting their perceived color is a daunting task at best. Colorimetry is designed mainly for the evaluation of uniform, flat, opaque, materials of fairly large size viewed on a medium-grey background under near-daylight sources of fairly high luminance. On the contrary, in situ teeth vary spatially, are curved and ridged, translucent, relatively small, and viewed against a variable background under nonuniform, and typically nonstandard, illumination. These differences in stimuli and viewing conditions summarize the difficulty in predicting the color appearance of teeth. SOURCES: The field of color science has extended basic colorimetry, as represented by CIE XYZ and CIELAB coordinates, to more complex visual stimuli and viewing environments. The CIECAM02 color appearance model accurately addresses issues of chromatic adaptation, luminance effects and adaptation, background and surround effects, and the higher dimensionality of color appearance. Such models represent a significant advance and are used successfully in a variety of applications. However, many stimuli vary in space and time at scales not addressed by typical color appearance models. For example, high-definition video images would fall into such a category and so would in situ human teeth. More recently, color appearance models and image quality metrics have been combined to create image appearance models for even more complex visual stimuli. CONCLUSIONS: This paper provides an overview of fundamental and advanced colorimetry leading up to color appearance and image appearance models and their potential application in dentistry.