时空遥感影像融合研究的进展与趋势  

Research Progress and Trend of Spatial and Temporal Remote Sensing Image Fusion

作　　者：黄波[1,2,3] HUANG Bo(Department of Geography and Resource Management,The Chinese University of Hong Kong,Hong Kong 999079;Institute of Space and Earth Information Science,The Chinese University of Hong Kong,Hong Kong 999079;Shenzhen Research Institute,The Chinese University of Hong Kong,Shenzhen 518057,Guangdong)

机构地区：[1]香港中文大学地理与资源管理学系,香港999079 [2]香港中文大学太空与地球信息科学研究所,香港999079 [3]香港中文大学深圳研究院,广东深圳518057

出　　处：《四川师范大学学报（自然科学版）》2020年第4期427-434,F0002,共9页Journal of Sichuan Normal University（Natural Science）

基　　金：国家自然科学基金(41371417)。

摘　　要：地表与大气环境的实时精细监测需要高时空分辨率的遥感影像提供数据支撑,然而,现有单一卫星传感器无法获取同时具有高空间与高时间分辨率的遥感影像.针对这一问题,国内外学者提出了大量的时空遥感影像融合算法,以低成本、便捷高效地生成满足不同应用需求的高时空分辨率遥感影像.总结现有主要的时空遥感影像融合算法并基于不同的算法原理将其分为4类:1)基于空间信息分解的融合方法,2)基于时空变化滤波的融合方法,3)基于学习的融合方法,4)组合性的融合方法.同时,讨论时空遥感影像融合的不确定性问题,并对其未来的发展趋势提出前瞻性的展望.Real-time and fine monitoring of land surface and atmospheric environment requires remote sensing images with both high spatial and high temporal resolution as data support.However,data from a single satellite sensor are unable to satisfy our demand.Therefore,plenty of spatial and temporal image fusion algorithms have been proposed to produce the images with high spatiotemporal resolution.This paper summarizes the existing main fusion methods and classifies them into four categories:1)spatial unmixing-based fusion method,2)sptaio-temporal filter-based fusion method,3)learning-based fusion method,and 4)hybrid fusion method.Besides,the uncertainties of the spatial and temporal remote sensing image fusion are discussed.Further,this paper prospects the future trend of the spatial and temporal image fusion.

关 键 词：时空融合 遥感影像 不确定性 时间分辨率 空间分辨率 

分 类 号：P237[天文地球—摄影测量与遥感]