测绘学报 ›› 2023, Vol. 52 ›› Issue (7): 1074-1089.doi: 10.11947/j.AGCS.2023.20220499
张兵1,2, 高连如1,3, 李嘉鑫1,2,3, 洪丹枫1,3, 郑珂1,3
收稿日期:
2022-08-22
修回日期:
2023-06-20
发布日期:
2023-07-31
作者简介:
张兵(1969-),男,博士,研究员,研究方向为高光谱遥感与遥感大数据。E-mail:zb@radi.ac.cn
基金资助:
ZHANG Bing1,2, GAO Lianru1,3, LI Jiaxin1,2,3, HONG Danfeng1,3, ZHENG Ke1,3
Received:
2022-08-22
Revised:
2023-06-20
Published:
2023-07-31
Supported by:
摘要: 高光谱图像作为多模态遥感数据的重要组成部分,能够捕捉地物精细的光谱特征。由于成像机理的限制,空间细节的损失导致高光谱图像的空间表征能力有所退化,一定程度上限制了数据进一步应用的潜力。数据融合是解决空间/光谱分辨率矛盾的有效手段,近年来相关理论得到了深入发展。本文全面综述了高/多光谱遥感图像超分辨率融合领域的研究进展与展望。首先,将当前方法系统性地分为细节注入、模型优化及深度学习3大类方法,并对不同方法的原理、模型、代表性算法进行了回顾,重点介绍了模型优化中的矩阵分解、张量表示及深度学习中的监督与非监督方法。在此基础上,梳理了该领域技术在像素级分类、目标提取、在轨融合领域的成功应用案例,指出融合产品的潜能在后续遥感应用未被充分挖掘的现状;然后,从退化模型、数据-模型驱动、多任务一体化及应用耦合4个角度对该领域进行展望;最后,就该领域的研究现状与发展趋势进行总结,归纳各类方法优劣势的同时,点明了多类方法协同、外部数据辅助及实际应用驱动等方面的重要性。
中图分类号:
张兵, 高连如, 李嘉鑫, 洪丹枫, 郑珂. 高/多光谱遥感图像超分辨率融合研究进展与展望[J]. 测绘学报, 2023, 52(7): 1074-1089.
ZHANG Bing, GAO Lianru, LI Jiaxin, HONG Danfeng, ZHENG Ke. Advances and prospects in hyperspectral and multispectral remote sensing image super-resolution fusion[J]. Acta Geodaetica et Cartographica Sinica, 2023, 52(7): 1074-1089.
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