Color by Correlation: A Simple, Unifying Framework for Color Constancy
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Computer Graphics and Applications
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part IV
Outex - New Framework for Empirical Evaluation of Texture Analysis Algorithms
ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 1 - Volume 1
On the Removal of Shadows from Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
A color image segmentation approach for content-based image retrieval
Pattern Recognition
Color temperature estimation of scene illumination by the sensor correlation method
Systems and Computers in Japan
Illuminant Change Estimation via Minimization of Color Histogram Divergence
Computational Color Imaging
Intrinsic images by Fisher linear discriminant
ISVC'07 Proceedings of the 3rd international conference on Advances in visual computing - Volume Part II
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Planckian illuminants and von Kries diagonal model are commonly assumed by many computer vision algorithms for modeling the color variations between two images of a same scene captured under two different illuminants. Here we present a method to estimate a von Kries transform approximating a Planckian illuminant change and we show that the Planckian assumption constraints the von Kries coefficients to belong to a ruled surface, that depends on physical cues of the lights. Moreover, we provide an approximated parametric representation of such a surface, making evident the dependence of the von Kries transform on the light color temperature and on the intensity.