CHALLENGES OF REMOTE SENSING IMAGE FUSION TO OPTIMIZE EARTH OBSERVATION DATA EXPLOITATION

Abstract

Remote sensing delivers multi-modal and -temporal data. Image fusion is a valuable tool to optimize multisensor image exploitation. It has developed into a usable image processing technique to extract information of higher quality and reliability. Due to the availability of many different sensors and operational image fusion techniques researchers have conducted a vast amount of successful experiments. However, the definition of an appropriate workflow prior to processing the imagery requires knowledge in all related fields, i.e. remote sensing, image fusion and the desired image exploitation processing. From the results it is visible that the choice of the appropriate technique as well as the fine tuning of the individual parameters of this technique is crucial. There is still a lack of strategic guidelines due to its complexity and variability. This paper reports on the findings of an initiative to streamline data selection, application requirements and the choice of a suitable image fusion technique. All this forms the first step into the development a Fusion Approach Selection Tool (FAST). The project aims at collecting successful image fusion cases that are relevant to other users and other areas of interest. From there standards will be developed that apply to these cases that are valuable contributions to further applications and developments. The availability of these standards will help to further develop image fusion techniques, make best use of existing multimodal images and provide new insights on the processes of the Earth.