The iCAM Framework for Image Appearance, Image Differences, and Image Quality

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 these models. 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. This paper reviews the concepts of image appearance modeling, presents iCAM as one example of such a model, and provides a number of examples of the use of iCAM in image reproduction and image quality evaluation.