Reflectance Perception is an image processing software that intelligently compensates for illumination problems in digital pictures. Reflectance Perception has been developed at the Robotics Institute of Carnegie Mellon University to enable machines to approach the visual capabilities of the human eye. Users will find that the results of Reflectance Perception resemble what their eyes would see if they viewed the environment instead of a camera.

From the original image the software estimates the illumination field that illuminated the scene when the picture was taken. Then it corrects every pixel to produce a result that would have been seen if the scene was uniformly illuminated. The algorithm is intelligent in that it automatically “finds” where shadows start and stop just by “looking” at the original picture. By knowing where the shadow boundaries are, Reflectance Perception produces results free of a highly objectionable artifact known as “halo”.

Commonly used tools to compensate for shadows in originals include brightness/contrast adjustment, gamma adjustment and histogram equalization. Advanced users of Photoshop or similar photo editing packages could go through a tedious sequence of steps to “mask” objects from the shadows and then selectively change the brightness of one or the other. The difference is that with Reflectance Perception, (a) it is an automatic, ‘one-click’ process, (b) the results are superior to anything currently available on the market, (c) other tools “illuminate” the whole image; Reflectance Perception illuminates only what needs to be illuminated, and (d) other methods create shift in colors, or create “halos” or “auras” around the object/shadow boundary.