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Lightness, Brightness and Transparency
This volume deals with the visual perception of lightness, brightness, and transparency of surfaces, both under minimal laboratory conditions and in complex images typical of everyday life.
336 pages, Kindle Edition
First published September 1, 1994
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About the author
Alan L. Gilchrist
2 books1 followerAlan Gilchrist is a Professor in the Faculty of Psychology at Rutgers University in the USA.
"I study visual perception, especially the perception of surface color, and especially the black-white dimension. Vision is known to be based on the image projected onto the retina, but the problem of how to assign black, white and gray values to surfaces represented in that image remains unsolved, in human vision as in computer vision. Because of variations in many factors such as the background of a surface and the lighting conditions, the perception of any one specific surface color can be associated with many patterns of local stimulation at the retina. The goal of the work is to describe the software (not the hardware, or wetware) used by the visual system to decode the retinal image. The primary method is psychophysics. Naive observers are exposed to displays specially constructed so that competing theories make opposing predictions of what observers will see. The observer reports, typically involving matches made using a color chart, are then used to evaluate theories. In my lab we have approached this problem in two ways. In earlier work, an inverse-optics approach was taken in which we attempted to determine the computations necessary to recover objective properties like surface color. More recent work has focused on the pattern of errors shown by human observers when judging surface colors. These errors are systematic, not random, and the work is based on the assumption that the pattern of errors is the signature of the software used to decode the retinal image."
"I study visual perception, especially the perception of surface color, and especially the black-white dimension. Vision is known to be based on the image projected onto the retina, but the problem of how to assign black, white and gray values to surfaces represented in that image remains unsolved, in human vision as in computer vision. Because of variations in many factors such as the background of a surface and the lighting conditions, the perception of any one specific surface color can be associated with many patterns of local stimulation at the retina. The goal of the work is to describe the software (not the hardware, or wetware) used by the visual system to decode the retinal image. The primary method is psychophysics. Naive observers are exposed to displays specially constructed so that competing theories make opposing predictions of what observers will see. The observer reports, typically involving matches made using a color chart, are then used to evaluate theories. In my lab we have approached this problem in two ways. In earlier work, an inverse-optics approach was taken in which we attempted to determine the computations necessary to recover objective properties like surface color. More recent work has focused on the pattern of errors shown by human observers when judging surface colors. These errors are systematic, not random, and the work is based on the assumption that the pattern of errors is the signature of the software used to decode the retinal image."
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