Abstract: In this paper, a new wavelet representation for multimodal images is presented. The idea for this representation is based on the first fundamental form that provides a local measure for the contrast of a multimodal image. In this paper, this concept is extended towards multiscale fundamental forms using the dyadic wavelet transform of Mallat. The multiscale fundamental forms provide a local measure for the contrast of a multimodal image at different scales. The representation allows for a multiscale edge description of multimodal images. Two applications are presented: multispectral image fusion and colour image noise filtering. In an experimental section, the presented techniques are compared to single valued and/or single scale algorithms that were previously described in the literature. The techniques, based on the new representation are demonstrated to out-perform the others.