Skip to main content

Estimating Illumination Chromaticity via Support Vector Regression

Resource type
Date created
Author: Funt, Brian
The technique of support vector regression is applied to the problem of estimating the chromaticity of the light illuminating a scene from a color histogram of an image of the scene. Illumination estimation is fundamental to white balancing digital color images and to understanding human color constancy. Under controlled experimental conditions, the support vector method is shown to perform better than the neural network and color by correlation methods.
Presented at the CIC 2004 IS&T/SID Color Imaging Conference, Nov. 2004.
Published as
Funt, B., and Xiong, W., "Estimating Illumination Chromaticity via Support Vector Regression," Proc. Twelfth IS&T/SID Color Imaging Conference: Color Science, Systems & Applications, Scottsdale, AZ. Nov. 2004.
Copyright statement
Copyright is held by the author(s).
Scholarly level
Peer reviewed?
Member of collection
Download file Size
Funt_Xiong_SVR_IllumEst_CIC12.pdf 157.49 KB

Views & downloads - as of June 2023

Views: 25
Downloads: 2