iCAM framework for image appearance, differences, and quality

Abstract

Traditional color appearance modeling has recently matured to the point that available, internationally recommended models such as CIECAM02 are capable of making a wide range of predictions, to within the observer variability in color matching and color scaling of stimuli, in somewhat simplified viewing conditions. It is proposed that the next significant advances in the field of color appearance modeling and image quality metrics will not come from evolutionary revisions of colorimetric color appearance models alone. Instead, a more revolutionary approach will be required to make appearance and difference predictions for more complex stimuli in a wider array of viewing conditions. Such an approach can be considered image appearance modeling, since it extends the concepts of color appearance modeling to stimuli and viewing environments that are spatially and temporally at the level of complexity of real natural and man-made scenes, and extends traditional image quality metrics into the color appearance domain. Thus, two previously parallel and evolving research areas are combined in a new way as an attempt to instigate a significant advance. We review the concepts of image appearance modeling, present iCAM as one example of such a model, and provide a number of examples of the use of iCAM in image reproduction and image quality evaluation.