Multiscale fundamental forms: a multimodal image wavelet representation

Abstract

A new wavelet representation for multimodal images is presented. The idea for this representation is based on the first fundamental that provides a local measure for the contrast of a multimodal image. 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 outperform the others.