Hyperspectral and multispectral remote sensing image fusion using SwinGAN with joint adaptive spatial-spectral gradient loss function-Reference-Cited by-同舟云学术

Hyperspectral and multispectral remote sensing image fusion using SwinGAN with joint adaptive spatial-spectral gradient loss function

Published:2023-09-04 Issue:1 Volume:16 Page:3580-3600
ISSN:1753-8947
Container-title:International Journal of Digital Earth
language:en
Short-container-title:International Journal of Digital Earth

Author:

Zhu Chunyu¹,Deng Shangqi²,Li Jiaxin³⁴,Zhang Ying¹,Gong Liwei¹,Gao Liangbo¹,Ta Na¹,Chen Shengbo¹,Wu Qiong¹

Affiliation:

1. College of Geo-Exploration Science and Technology, Jilin University, Changchun, People’s Republic of China

2. School of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu, People’s Republic of China

3. Key Laboratory of Computational Optical Imaging Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, People’s Republic of China

4. College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, People’s Republic of China

Funder

National Key Research and Development Program of China

Publisher

Informa UK Limited

Subject

General Earth and Planetary Sciences,Computer Science Applications,Software

Link

https://www.tandfonline.com/doi/pdf/10.1080/17538947.2023.2253206

Reference60 articles.

1. Improving Component Substitution Pansharpening Through Multivariate Regression of MS $+$Pan Data

2. Hyperspectral Pansharpening Based on Improved Deep Image Prior and Residual Reconstruction

3. Pansharpening approach via two-stream detail injection based on relativistic generative adversarial networks

4. Fusion of Hyperspectral and Multispectral Images: A Novel Framework Based on Generalization of Pan-Sharpening Methods

5. Hyperspectral and LiDAR Data Fusion: Outcome of the 2013 GRSS Data Fusion Contest

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