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Learning color-appearance models by means of feed-forward neural networks

✍ Scribed by P. Campadelli; C. Gangai; R. Schettini

Publisher
John Wiley and Sons
Year
1999
Tongue
English
Weight
525 KB
Volume
24
Category
Article
ISSN
0361-2317

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✦ Synopsis

Device-independent color imaging demands a reliable color-appearance model. We present a method for faithfully approximating color-appearance models by means of feed-forward neural networks trained with the error back-propagation algorithm. In particular, we present experimental evidence that in several "standard" viewing conditions recommended for testing color-appearance models, the same network architecture is capable of learning quite satisfactorily the transformations performed by different color-appearance models.

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