There has been a revivification of interest in the Retinex computation in the last six or seven years, especially in its use for image enhancement. In his last published concept (1986) for a Retinex computation, Land introduced a center/surround spatial form, which was inspired by the receptive field structures of neurophysiology. With this as our starting point, we develop the Retinex concept into a full scale automatic image enhancement algorithm—the multiscale Retinex with color restoration (MSRCR)—which combines color constancy with local contrast/lightness enhancement to transform digital images into renditions that approach the realism of direct scene observation. Recently, we have been exploring the fundamental scientific questions raised by this form of image processing. 1. Is the linear representation of digital images adequate in visual terms in capturing the wide scene dynamic range? 2. Can visual quality measures using the MSRCR be developed? 3. Is there a canonical, i.e., statistically ideal, visual image? The answers to these questions can serve as the basis for automating visual assessment schemes, which, in turn, are a primitive first step in bringing visual intelligence to computers.