Overview of multi-modal remote sensing image matching methods

doi:10.11947/j.AGCS.2022.20220126

Abstract

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:

P237

SUI Haigang, LIU Chang, GAN Zhe, JIANG Zhengjie, XU Chuan. Overview of multi-modal remote sensing image matching methods[J]. Acta Geodaetica et Cartographica Sinica, 2022, 51(9): 1848-1861.

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