[1]荣兰,成科扬,蒋森林,等.CCFAI:基于深度学习的遥感图像超分辨率重建技术综述[J].郑州大学学报(工学版),2022,43(05):8-16.
 CCFAI: Survey Of Deep-Learning Approaches For Remote Sensing Super-Resolution Reconstruction[J].Journal of Zhengzhou University (Engineering Science),2022,43(05):8-16.
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CCFAI:基于深度学习的遥感图像超分辨率重建技术综述()
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《郑州大学学报(工学版)》[ISSN:1671-6833/CN:41-1339/T]

卷:
43
期数:
2022年05期
页码:
8-16
栏目:
出版日期:
2022-08-22

文章信息/Info

Title:
CCFAI: Survey Of Deep-Learning Approaches For Remote Sensing Super-Resolution Reconstruction
作者:
荣兰成科扬蒋森林詹永照
文献标志码:
A
摘要:
遥感图像超分辨率重建技术是计算机视觉中的重要技术。近年来,得益于深度学习的成功,基于深度学习的遥感图像超分辨率技术正在蓬勃发展,在许多领域被广泛应用。本文首先回顾传统遥感图像超分重建算法并引出基于深度学习的遥感图像超分重建方法;然后总结了单幅遥感图像、多幅遥感图像和多/高光谱遥感图像超分重建方法中具有代表性的基于深度学习的方法,我们从模型类型、网络结构和重建效果等方面对各种方法进行分析和评价,并对比了它们的优缺点;最后对遥感图像超分重建技术存在的问题进行分析和未来的发展做出展望。
Abstract:
Super-resolution reconstruction of remote sensing image is an important technique to improve the resolution of remote sensing image in computer vision.In recent years, thanks to the success of deep learning, remote sensing image super-resolution technology ba<x>sed on deep learning is booming and widely used in many fields.Firstly,we review the traditional remote sensing image super-resolution reconstruction algorithm and introduces the remote sensing image super-resolution reconstruction method ba<x>sed on deep learning.Then, we summarize the representative deep learn ba<x>sed methods for the super-resolution reconstruction of single remote sensing image, multiple remote sensing image and multi-hyperspectral remote sensing image. We analyze and evaluate the various methods from the aspects of model type, network structure and reconstruction effect, and compare their advantages and disadvantages.Finally, Finally, we analyze the existing problems of remote sensing image super-resolution reconstruction technology and give the prospect of its future development.
更新日期/Last Update: 2022-08-20