Acta Geodaetica et Cartographica Sinica ›› 2022, Vol. 51 ›› Issue (9): 1848-1861.doi: 10.11947/j.AGCS.2022.20220126

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Overview of multi-modal remote sensing image matching methods

SUI Haigang1, LIU Chang1, GAN Zhe2, JIANG Zhengjie3, XU Chuan4   

  1. 1. State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China;
    2. Troops 93114, Beijing 100089, China;
    3. School of Information and Electronics, Beijing Institute of Technology, Beijing 100081, China;
    4. School of Computer Science, Hubei University of Technology, Wuhan 430068, China
  • Received:2022-02-24 Revised:2022-07-24 Published:2022-09-29
  • Supported by:
    The Guangxi Science and Technology Major Project (No. AA22068072); The National Natural Science Foundation of China(Nos.41771457; 41601443)

Abstract: Remote sensing image matching is the key foundation of remote sensing image processing, which has been a research hotspot for scholars at home and abroad. Due to the characteristics of multi-modal images such as radiation difference, geometric difference, scale difference, viewpoint difference and dimensional difference, a universal matching method with strong universality has not yet appeared. With the continuous development of remote sensing, artificial intelligence, big data, and other technologies and the continuous expansion of application fields, the image matching technology system is also developing and evolving. This paper summarizes the multi-modal remote sensing image matching classification system based on the development history of image matching technology, discusses the latest progress of multi-modal image matching technology from the perspective of feature-driven and data-driven, and points out the core difficulties and future development trend in order to promote the deeper development of multi-modal image matching research.

Key words: image matching, multi-modal, feature description, deep learning

CLC Number: