Image Fusion-The ARSIS Concept and Some Successful Implementation

This article aims at explaining the ARSIS concept. By fusing two sets of images A and B, one with a high spatial resolution, the other with a low spatial resolution and different spectral bands, the ARSIS concept permits to synthesise the dataset B at the resolution of A that is as close as possible to reality. It is based on the assumption that the missing information is linked to the high frequencies in the sets A and B. It searches a relationship between the high frequencies in the multispectral set B and the set A and models this relationship. The general problem for the synthesis is presented first. The general properties of the fused product are given. Then, the ARSIS concept is discussed. The general scheme for the implementation of a method belonging to this concept is presented. Then, this article intends to help practitioners and researchers to better understand this concept through practical details about implementations. Two Multiscale Models are described as well as two Inter-Band Structure Models (IBSM). They are applied to an Ikonos image as an illustration case. The fused products are assessed by means of a known protocol comprising a series of qualitative and quantitative tests. The products are found of satisfactory quality. This case illustrates the differences existing between the various models, their advantages and limits. Tracks for future improvements are discussed.