多模态遥感图像匹配方法综述

Overview of multi-modal remote sensing image matching methods

遥感图像匹配是遥感图像处理的关键基础,一直是国内外学者研究的热点。由于多模态图像具有辐射差异、几何差异、尺度差异、视角差异、维度差异等特性,目前尚未出现一种普适性强的通用匹配方法。随着遥感、人工智能、大数据等技术的不断发展和应用领域的持续拓展,图像匹配技术体系也在不断地发展和演化。本文在系统梳理图像匹配技术发展历程的基础上,对多模态遥感图像匹配分类体系进行了归纳总结,从特征驱动和数据驱动两方面论述了多模态图像匹配技术研究的最新进展,并指出其面临的核心困难及未来发展趋势,以期推动多模态图像匹配研究更加深入发展。

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.