Multiple Deep Proximal Learning for Hyperspectral-Multispectral Image Fusion-Reference-Cited by-同舟云学术

Multiple Deep Proximal Learning for Hyperspectral-Multispectral Image Fusion

Published:2023 Issue: Volume:61 Page:1-14
ISSN:0196-2892
Container-title:IEEE Transactions on Geoscience and Remote Sensing
language:
Short-container-title:IEEE Trans. Geosci. Remote Sensing

Author:

Yang Jingxiang¹^ORCID,Lin Tian¹^ORCID,Chen Xiaoyang¹^ORCID,Xiao Liang²^ORCID

Affiliation:

1. School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China

2. School of Computer Science and Engineering and the Jiangsu Key Laboratory of Spectral Imaging and Intelligent Sense, Nanjing University of Science and Technology, Nanjing, China

Funder

National Natural Science Foundation of China

Natural Science Foundation of Jiangsu Province

Jiangsu Provincial Social Developing Project

Jiangsu Geological Bureau Research Project

Fundamental Research Funds for the Central Universities

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Earth and Planetary Sciences,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/36/10006360/10262322.pdf?arnumber=10262322

Reference55 articles.

1. Hyperspectral super-resolution via coupled tensor ring factorization

2. Fusing Hyperspectral and Multispectral Images via Coupled Sparse Tensor Factorization

3. Learning a Low Tensor-Train Rank Representation for Hyperspectral Image Super-Resolution

4. Hyperspectral Images Super-Resolution via Learning High-Order Coupled Tensor Ring Representation

5. What is the space of spectral sensitivity functions for digital color cameras?

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