Over the past few decades, with the rapid development of global aerospace and aerial remote sensing technology, the types of sensors have evolved from the traditional monomodal sensors (e.g., optical sensors) to the new generation of multimodal sensors [e.g., multispectral, hyperspectral, light detection and ranging (LiDAR) and synthetic aperture radar (SAR) sensors]. These advanced devices can dynamically provide various and abundant multimodal remote sensing images with different spatial, temporal, and spectral resolutions according to different application requirements. Since then, it is of great scientific significance to carry out the research of multimodal remote sensing image registration, which is a crucial step for integrating the complementary information among multimodal data and making comprehensive observations and analysis of the Earths surface. In this work, we will present our own contributions to the field of multimodal image registration, summarize the advantages and limitations of existing multimodal image registration methods, and then discuss the remaining challenges and make a forward-looking prospect for the future development of the field.

翻译：过去几十年来，随着全球航空航天遥感技术的快速发展，传感器类型已从传统单模态传感器（如光学传感器）演变为新一代多模态传感器[例如多光谱、高光谱、激光雷达（LiDAR）和合成孔径雷达（SAR）传感器]。这些先进设备能够根据不同应用需求动态提供具有不同空间、时间和光谱分辨率的多样化、丰富的多模态遥感图像。因此，开展多模态遥感图像配准研究具有重要的科学意义，该技术是整合多模态数据间的互补信息、实现对地球表面综合观测与分析的关键步骤。本文介绍了我们在多模态图像配准领域的研究贡献，总结了现有方法的优势与局限性，进而探讨了当前存在的挑战，并对该领域的未来发展进行了前瞻性展望。