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Proceedings Paper

Implementing color transformation across media based on color appearance model by neural networks
Author(s): Binghua Chai; Ningfang Liao; Dazun Zhao
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Paper Abstract

Interest in color appearance models (CAM) has been greatly stimulated recently by the need in handling digital images. This article demonstrates that a multi-layers feed-forward artificial neural network with the error back-propagation algorithm was used to approximate color appearance model CIECAM02 with different white points and different media. For the prediction of the forward and inverse model respectively, in order to realize accurate mapping, especially to the inverse model, color spaces conversion between input color space and output color space (that is cylindrical coordinates and rectangular coordinates) was implemented before training the neural networks. Meanwhile we approximated the combination of the forward and inverse CIECAM02 models employing a neural network for different conditions including whites (D65 or D50) and media (booth and CRT) in order to realize the color transformation from one medium to another conveniently. The experimental results indicated that the prediction could satisfy the accuracy requirement. So in practice we can choose these two kinds of different prediction ways to meet our need according to different situations.

Paper Details

Date Published: 8 February 2005
PDF: 8 pages
Proc. SPIE 5637, Electronic Imaging and Multimedia Technology IV, (8 February 2005); doi: 10.1117/12.570757
Show Author Affiliations
Binghua Chai, Beijing Institute of Technology (China)
Ningfang Liao, Beijing Institute of Technology (China)
Dazun Zhao, Beijing Institute of Technology (China)

Published in SPIE Proceedings Vol. 5637:
Electronic Imaging and Multimedia Technology IV
Chung-Sheng Li; Minerva M. Yeung, Editor(s)

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