You may have access to the free features available through My Research. You can save searches, save documents, create alerts and more. Please log in through your library or institution to check if you have access.
If you log in through your library or institution you might have access to this article in multiple languages.
Styles include MLA, APA, Chicago and many more. This feature may be available for free if you log in through your library or institution.
You may have access to it for free by logging in through your library or institution.
You may have access to different export options including Google Drive and Microsoft OneDrive and citation management tools like RefWorks and EasyBib. Try logging in through your library or institution to get access to these tools.
Alternate 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.
