Estimating the color of the illuminant under which an image of a scene was captured is a central part of solving the color constancy problem: that is, of deriving an illuminant independent representation of the reflectance's in a scene. In this article we develop a general correlation framework for solving the illuminant estimation problem. Within this framework estimation is posed as a correlation of the colors in an image with the colors that can occur under each of a set of possible lights. Rather than attempting to recover a single estimate of the illuminant as many previous authors have done, we, in the first instance, recover a correlation measure for each possible illuminant. We then select an estimate of the scene illuminant based on these correlations. The work presented here follows from previously published work.¹ In this article we extend that work by showing that the correlation framework is rich enough to allow many existing algorithms to be expressed within it. In particular the grey-world, max-RGB, gamut mapping, and Maloney–Wandell algorithms, perhaps the algorithms most widely cited in the literature, are presented in this correlation framework. This work together with work published elsewhere² shows that almost all published algorithms based on a Mondriaan world can be formulated in the framework presented here.