A Review of Hyperspectral Image Super-Resolution Based on Deep Learning
文献类型：期刊论文
| 作者 | C. Chen, Y. C. Wang, N. Zhang, Y. X. Zhang and Z. K. Zhao |
| 刊名 | Remote Sensing
 |
| 出版日期 | 2023 |
| 卷号 | 15期号:11页码:36 |
| DOI | 10.3390/rs15112853 |
| 英文摘要 | Hyperspectral image (HSI) super-resolution (SR) is a classical computer vision task that aims to accomplish the conversion of images from lower to higher resolutions. With the booming development of deep learning (DL) technology, more and more researchers are dedicated to the research of image SR techniques based on DL and have made remarkable progress. However, no scholar has provided a comprehensive review of the field. As a response, in this paper we aim to supply a comprehensive summary of the DL-based SR techniques for HSI, including upsampling frameworks, upsampling methods, network design, loss functions, representative works with different strategies, and future directions, in which we design several sets of comparative experiments for the advantages and limitations of two-dimensional convolution and three-dimensional convolution in the field of HSI SR and analyze the experimental results in depth. In addition, the paper also briefly discusses the secondary foci such as common datasets, evaluation metrics, and traditional SR algorithms. To the best of our knowledge, this paper is the first review on DL-based HSI SR. |
| URL标识 | 查看原文 |
| 语种 | 英语 |
| 源URL | [http://ir.ciomp.ac.cn/handle/181722/67362]  |
| 专题 | 中国科学院长春光学精密机械与物理研究所 |
| 推荐引用方式 GB/T 7714 | C. Chen, Y. C. Wang, N. Zhang, Y. X. Zhang and Z. K. Zhao. A Review of Hyperspectral Image Super-Resolution Based on Deep Learning[J]. Remote Sensing,2023,15(11):36. |
| APA | C. Chen, Y. C. Wang, N. Zhang, Y. X. Zhang and Z. K. Zhao.(2023).A Review of Hyperspectral Image Super-Resolution Based on Deep Learning.Remote Sensing,15(11),36. |
| MLA | C. Chen, Y. C. Wang, N. Zhang, Y. X. Zhang and Z. K. Zhao."A Review of Hyperspectral Image Super-Resolution Based on Deep Learning".Remote Sensing 15.11(2023):36. |
入库方式： OAI收割
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。