Retinex processing for automatic image enhancement

Abstract

In the last published concept (1986) for a Retinex computation, Edwin Land introduced a center/surround spatial form, which was inspired by the receptive field structures of neurophysiology. With this as our starting point we have over the years developed this concept into a full scale automatic image enhancement algorithm - the Multi-Scale 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. The MSRCR algorithm has proven to be quite general purpose, and very resilient to common forms of image pre-processing such as reasonable ranges of gamma and contrast stretch transformations. More recently we have been exploring the fundamental scientific implications of this form of image processing, namely: (i) the visual inadequacy of the linear representation of digital images, (ii) the existence of a canonical or statistical ideal visual image, and (iii) new measures of visual quality based upon these insights derived from our extensive experience with MSRCR enhanced images. The lattermost serves as the basis for future schemes for automating visual assessment - a primitive first step in bringing visual intelligence to computers.