The determination of relative pose between two range images, also called registration, is a ubiquitous problem in computer vision, for geometric model building as well as dimensional inspection. The method presented in this paper takes advantage of the ability of many active optical range sensors to record intensity or even color in addition to the range information. This information is used to improve the registration procedure by constraining potential matches between pairs of points based on a similarity measure derived from the intensity information. One difficulty in using the intensity information is its dependence on the measuring conditions such as distance and orientation. The intensity or color information must first be converted into a viewpoint-independent feature. This can be achieved by inverting an illumination model, by differential feature measurements or by simple clustering. Following that step, a robust iterative closest point method is then used to perform the pose determination. Using the intensity can help to speed up convergence or, in cases of remaining degrees of freedom (e.g. on images of a sphere), to additionally constrain the match. The paper will describe the algorithmic framework and provide examples using range-and-color images.