9. An automatic image registration system comprising: an input arranged to receive a first image and a second image, the first and second images being of objects and with at least part of one object being common to the first and second images; a processor arranged to compute semantic information for each of the first and second images, the semantic information comprising information about types of the objects in the first and second images and a certainty of the semantic information, computing the semantic information comprising using a regression forest comprising a plurality of regression trees each having been trained to produce semantic information; the processor further arranged to find a mapping to register the first and second images, the mapping taking into account intensities of image elements of the first and second images and also taking into account the semantic information in a manner which is weighted by the certainty of the semantic information; and the processor further arranged to register the first and second images based at least in part on minimizing an energy function, the energy function comprising: a summation of a term related to a Kullback-Leibler divergence and a summation of a term related to a marginal entropy of the first image and a term related to a marginal entropy of the second image, less a term related to a joint entropy of the first and second images.
9. An automatic image registration system comprising: an input arranged to receive a first image and a second image, the first and second images being of objects and with at least part of one object being common to the first and second images; a processor arranged to compute semantic information for each of the first and second images, the semantic information comprising information about types of the objects in the first and second images and a certainty of the semantic information, computing the semantic information comprising using a regression forest comprising a plurality of regression trees each having been trained to produce semantic information; the processor further arranged to find a mapping to register the first and second images, the mapping taking into account intensities of image elements of the first and second images and also taking into account the semantic information in a manner which is weighted by the certainty of the semantic information; and the processor further arranged to register the first and second images based at least in part on minimizing an energy function, the energy function comprising: a summation of a term related to a Kullback-Leibler divergence and a summation of a term related to a marginal entropy of the first image and a term related to a marginal entropy of the second image, less a term related to a joint entropy of the first and second images. 16. The system as claimed in claim 9 , the processor being further arranged to display, on a display device, at least the first image as a contour map overlaid on top of at least the second image, and to display, on the display device, at least the first image or the second image such that the color or transparency of the at least first image or the second image is related to an estimated uncertainty of a registration value.