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Proceedings Paper

End-user display calibration via support vector regression
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Paper Abstract

The technique of support vector regression (SVR) is applied to the color display calibration problem. Given a set of training data, SVR estimates a continuous-valued function encoding the fundamental interrelation between a given input and its corresponding output. This mapping can then be used to find an output value for a given input value not in the training data set. Here, SVR is applied directly to the display's non-linearized RGB digital input values to predict output CIELAB values. There are several different linear methods for calibrating different display technologies (GOG, Masking and Wyble). An advantage of using SVR for color calibration is that the end-user does not need to apply a different calibration model for each different display technology. We show that the same model can be used to calibrate CRT, LCD and DLP displays accurately. We also show that the accuracy of the model is comparable to that of the optimal linear transformation introduced by Funt et al.

Paper Details

Date Published: 16 January 2006
PDF: 6 pages
Proc. SPIE 6058, Color Imaging XI: Processing, Hardcopy, and Applications, 60580M (16 January 2006); doi: 10.1117/12.643655
Show Author Affiliations
Behnam Bastani, Hewlett-Packard Co. (United States)
Brian Funt, Simon Fraser Univ. (Canada)
Weihua Xiong, Simon Fraser Univ. (Canada)

Published in SPIE Proceedings Vol. 6058:
Color Imaging XI: Processing, Hardcopy, and Applications
Reiner Eschbach; Gabriel G. Marcu, Editor(s)

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