Linking the von Kries model to Wien’s law for the estimation of an illuminant invariant image

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.

► Under Wien’s law, the parameters of the von Kries model are related each to other.
► These relationships depend on some photometric cues of the acquisition device.
► We compute the von Kries parameters from pairs of images taken under Wien’s lights.
► We estimate the photometric camera cues from the von Kries parameters.
► We use the camera cues to compute an intrinsic illuminant invariant image.