In addition to colors and shapes, factors of material appearance such as glossiness, translucency, and roughness are important for reproducing the realistic feeling of images. In general, these perceptual qualities are often degraded when reproduced as digital color images. Therefore, it is useful to enhance and reproduce them. In this article, the authors propose a material appearance enhancement algorithm for digital color images. First, they focus on the change of pupil behaviors, which is the first of the early vision systems to recognize visual information. According to their psychophysiological measurement of pupil size during material observation, they find that careful observation of surface appearance causes the pupil size to contract further. Next, they reflect this property in the retinal response, which is the next system in early vision. Then, they construct a material appearance enhancement algorithm named “PuRet” based on these physiological models of pupil and retina. By applying the PuRet algorithm to digital color test images, they confirm that perceived material appearance, including glossiness, transparency, and roughness, in the images is enhanced by using their PuRet algorithm. Furthermore, they show possibilities to apply their algorithm to a material appearance management system that could produce equivalent appearance qualities among different imaging devices by adjusting one parameter of PuRet.