Improvements on a MMI-based method for automatic texture mapping of 3D dense models

Maximization of Mutual Information routines proved to be suitable for registration of multimodal images. Here a method is proposed to select, in a set of candidates, the image which has a closer resemblance with a given external one. Such algorithm is intended to serve within a wider scope procedure for the automatic texturing of 3D models, where the initial 2D-3D registration problem is shifted to a 2D-2D registration challenge. In order to improve its performance a number of variations in the way the Mutual Information is computed are introduced and a method to judge its reliability is proposed.