We found previous intensity-based techniques for automatically registering color images to three-dimensional laser scanned scenes to be inadequate. The similarity metric used to score the registration creates a number of local minima that inhibits searching via Powell?s Multidimensional Minimization Algorithm, a gradient-descent technique. To find the best metric for general environment scanning, we examine the results of different information-theoretic metrics. Our examination leads us to the conclusion that gradient-descent based techniques are not a good choice for unsupervised automatic registration for images from environment scans. However an unsupervised process is possible through global-optimization techniques at the cost of longer processing times.