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Proceedings Paper

Neural network method for characterizing video cameras
Author(s): Shuangquan Zhou; Dazun Zhao
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Paper Abstract

This paper presents a neural network method for characterizing color video camera. A multilayer feedforward network with the error back-propagation learning rule for training, is used as a nonlinear transformer to model a camera, which realizes a mapping from the CIELAB color space to RGB color space. With SONY video camera, D65 illuminant, Pritchard Spectroradiometer, 410 JIS color charts as training data and 36 charts as testing data, results show that the mean error of training data is 2.9 and that of testing data is 4.0 in a 2563 RGB space.

Paper Details

Date Published: 19 August 1998
PDF: 7 pages
Proc. SPIE 3561, Electronic Imaging and Multimedia Systems II, (19 August 1998); doi: 10.1117/12.319755
Show Author Affiliations
Shuangquan Zhou, Beijing Institute of Technology (China)
Dazun Zhao, Beijing Institute of Technology (China)

Published in SPIE Proceedings Vol. 3561:
Electronic Imaging and Multimedia Systems II
LiWei Zhou; Chung-Sheng Li, Editor(s)

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