A Fast and Robust Matching System for Multimodal Remote Sensing Image Registration

2021 
The rapid and explosive growth of remote sensing image dataset (e.g., optical, SAR, LiDAR) promotes the development of the aerospace industry. However, images with complex coverage scenes are usually captured by either different sensors from different perspectives or the same sensor in different periods [1]. These factors have brought a great challenge to precision image co-registration, and it is difficult to identify a fully universal method to cope with all registration cases. Any kind of image registration algorithm needs to consider the imaging principle, radiometric and geometric distortions, noise interference, and so on. To date, numerous efforts have been made to overcome these challenges and improve the performance of multimodal remote sensing image registration, which can be classified into three categories: area-based methods, feature-based methods and a joint of previous two categories [2].
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