End-user display calibration via support vector regression

Behnam Bastani; Brian Funt; Weihua Xiong

doi:10.1117/12.643655

16 January 2006 End-user display calibration via support vector regression

Behnam Bastani, Brian Funt, Weihua Xiong

Proceedings Volume 6058, Color Imaging XI: Processing, Hardcopy, and Applications; 60580M (2006) https://doi.org/10.1117/12.643655
Event: Electronic Imaging 2006, 2006, San Jose, California, United States

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.

Citation Download Citation

Behnam Bastani, Brian Funt, and Weihua Xiong "End-user display calibration via support vector regression", Proc. SPIE 6058, Color Imaging XI: Processing, Hardcopy, and Applications, 60580M (16 January 2006); https://doi.org/10.1117/12.643655

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