Lightness, or the perceived shade of gray of a surface, corresponds to the reflecting capacity of the object surface, called reflectance (white reflects 90%; black 3%). The basic problem in human lightness perception arises because the intensity of the light reflected from a surface to the eye (called luminance) depends on both its reflectance and the intensity of light illuminating it. Because of this, the luminance of a surface tells you nothing about its reflectance, as any luminance can come from any shade of gray. Helmholtz (
1866/1924) suggested that, in order to derive surface lightness, the visual system takes into account the amount of illumination reaching the surface but he did not specify how this is done. A more operational approach can be found in the anchoring theory (Gilchrist,
2006; Gilchrist et al.,
1999), which incorporates the key insight that the visual system does not need to know how much illumination a surface is getting—it only needs to know which surfaces are getting the same amount of illumination. Thus, if the visual system can group together surfaces that receive the same illumination, it can compute their lightness values simply by comparing the luminances of those surfaces, with no further reference to the illumination. A group of image regions representing surfaces under common illumination can be regarded as a frame of reference, as suggested earlier by Koffka (
1935). According to this gestalt approach, the retinal image is perceptually segmented into different frames of reference (frameworks), typically representing different levels of illumination.
In the research reported here, we tested the existence of functional frames of reference within a complex image using a novel technique for probing the computation of lightness at arbitrary positions in the image. Since the technique was first introduced by Gilchrist and his collaborators (Gilchrist & Radonjic,
2005), it has already been adopted by several laboratories (Bressan,
2006; Hillis & Brainard,
2007; Shapiro, Smith, & Knight,
2007). Small gray disks, each with the same standard luminance, are pasted into the image of a scene with complex illumination. The perceived lightness of each disk, quantified by observer matches to a standard scale, reveals the value computed by the visual system for that test luminance at that location in the image, much as the gauge figure of Koenderink, Van Doorn, and Kappers (
1992) reveals the perceived surface orientation at any arbitrary location in an image. When computed lightness for a standard luminance value is probed at multiple locations in an image, a map emerges showing areas within which computed lightness values are relatively homogeneous and locations where these values shift. By discovering where within an image the computed lightness value of a standard luminance changes, the probe disk technique can reveal those features of the image to which the visual system is most sensitive. If a region of the retinal image representing a field of illumination functions as a frame of reference for lightness, we would expect that probe disks pasted into that region of the image would appear to have roughly the same lightness value, and that lightness variations due to local background luminance would be small relative to variations from one framework to the next. If the region does not function as a frame of reference, probe disk appearance would correlate with some other metric, like disk/background luminance ratio, without regard to framework location.
Our main goal was to test the validity of the framework concept, in addition to other predictions based on the anchoring theory. Thus, a brief summary of the basic components of the anchoring theory will provide the necessary context for our experiments.