Color constancy based on local space average color

被引:101
作者
Ebner, Marc [1 ]
机构
[1] Univ Wurzburg, Lehrstuhl Informat 2, D-97074 Wurzburg, Germany
关键词
Color constancy; Space average color; Color perception; Vision; Color; Reflectance; Object recognition; RETINEX THEORY; LIGHTNESS; COMPUTATION; ALGORITHMS;
D O I
10.1007/s00138-008-0126-2
中图分类号
TP18 [人工智能理论];
学科分类号
140502 [人工智能];
摘要
Light, which is reflected from an object, varies with the type of illuminant used. Nevertheless, the color of an object appears to be approximately constant to a human observer. The ability to compute color constant descriptors from reflected light, is called color constancy. In order to solve the problem of color constancy, some assumptions have to be made. One frequently made assumption is that on average, the world is gray. We address the problem of color constancy and focus on the use of space average color for color constancy. Instead of computing global space average color we suggest to use local space average color as the illuminant frequently varies across an image. We discuss several different methods on how to compute local space average color. The performance of the different algorithms as well as related algorithms is evaluated on an object recognition task. Algorithms based on local space average color are simple, yet highly effective for the problem of color constancy. Such algorithms are particularly suited for object recognition tasks.
引用
收藏
页码:283 / 301
页数:19
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