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Seeing Black and White

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Gilchrist, Alan 作者
Oxford Univ Pr
译者
2006-5 出版日期
448 页数
$ 84.75 价格
HRD
丛书系列
9780195187168 图书编码

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发表于2024-09-20


Seeing Black and White 在线电子书 epub 下载 mobi 下载 pdf 下载 txt 下载 2024

Seeing Black and White 在线电子书 epub 下载 mobi 下载 pdf 下载 txt 下载 2024

Seeing Black and White 在线电子书 pdf 下载 txt下载 epub 下载 mobi 下载 2024



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Most people are surprised to learn that seeing has not yet been explained by science. Incredibly, scientists cannot even explain why some surfaces appear to be black while others appear to be white. The physical difference between a surface that appears to be black and one that appears to be white results from the percentage ot light that the object reflects, known as reflectance. A white surface reflects 30 times more light into the eye than a black surface. The amount of light reflected by a surface into the eye is, however, a product of more than its own reflectance; it is also a product of the intensity of illumination it receives. A sheet of white paper lying within a shadow can easily reflect the same absolute amount of light as a sheet of black paper lying outside the shadow. Thus, there is essentially no correlation between the amount of light reflected by a suface and its physical shade: a black paper in a bright light and a white paper in shadow reflect identical light to the eye. Still, the black paper appears to be black and the white paper appears to be white. How can it be? Somehow the visual system must use the surrounding context. But how? Good thinkers have struggled with this problem for over a thousand years, and the last 150 years have witnessed a sustained assault on the problem. In this volume, Alan Gilchrist, one of the leading researchers in achromatic perception, reviews the history of the scientific development of lightness theory from the nineteenth century until the present and outlines and critiques all the main theories of lightness, laying out the strengths and weaknesses of each. Based on thirty years of research, Gilchrist presents his own argument that previous models of lightness perception are too good because they fail to capture the errors and illusions present in human perception. These errors may contain crucial clues in the sense that the overall pattern of errors is the signature of the human visual system.

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