Estimating the Scene Illumination Chromaticity Using a Neural Network
Cardei, V., Funt, B. and Barnard, K., "Estimating the Scene
Illumination Chromaticity Using a Neural Network", Journal of the
Optical Society of America A, Vol. 19, No. 12, Dec 2002
Abstract:
A neural network can learn color constancy,
defined here as the ability to estimate the chromaticity of a scenes
overall illumination. We describe a multilayer neural network that is
able to recover the illumination chromaticity given only an image of
the scene. The network is previously trained by being presented with a
set of images of scenes and the chromaticities of the corresponding
scene illuminants. Experiments with real images show that the network
performs better than previous color constancy methods. In particular,
the performance is better for images with a relatively small number of
distinct colors. The method has application to machine vision problems
such as object recognition, where illumination-independent color
descriptors are required, and in digital photography, where
uncontrolled scene illumination can create an unwanted color cast in a
photograph.
Full text (pdf)
Keywords: Colour, digital image processing, vision and color,
color measurement, color vision
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