IEEE Computer Graphics and Applications
Is Machine Colour Constancy Good Enough?
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume I - Volume I
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
Color temperature estimation of scene illumination by the sensor correlation method
Systems and Computers in Japan
Estimating the spectral sensitivity of a digital sensor using calibration targets
Proceedings of the 9th annual conference on Genetic and evolutionary computation
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Modeling the color variation due to an illuminant change is an important task for many computer vision applications, like color constancy, object recognition, shadow removal and image restoration. The von Kries diagonal model and Wien's law are widely assumed by many algorithms for solving these problems. In this work we combine these two hypotheses and we show that under Wien's law, the parameters of the von Kries model are related to each other through the color temperatures of the illuminants and the spectral sensitivities of the acquisition device. Based on this result, we provide a method for estimating some camera cues that are used to compute the illuminant invariant intrinsic image proposed by Finlayson and others. This is obtained by projecting the log-chromaticities of an input color image onto a vector depending only on the spectral cues of the acquisition device.