This paper presents a method to efficiently compute the visibility of a 3D model seen from a series of calibrated georeferenced images. This is required to make methods aimed at enriching 3D models (finer reconstruction, texture mapping) based on such images scalable. The method consists in rasterizing the scene on the GPU from the point of views of the images with a known mapping between colors and scene elements. This pixel based visibility information is then made higher level by defining a set of geometric rules to select which images should be used when focusing on a given scene element. The visibility relation is finally used to build a visibility graph allowing for efficient sequential processing of the whole scene.