CODE-IF: A Convex/Deep Image Fusion Algorithm for Efficient Hyperspectral Super-Resolution-Reference-Cited by-同舟云学术

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CODE-IF: A Convex/Deep Image Fusion Algorithm for Efficient Hyperspectral Super-Resolution

Published:2024 Issue: Volume:62 Page:1-18
ISSN:0196-2892
Container-title:IEEE Transactions on Geoscience and Remote Sensing
language:
Short-container-title:IEEE Trans. Geosci. Remote Sensing

Author:

Lin Chia-Hsiang¹^ORCID,Hsieh Cheng-Ying²,Lin Jhao-Ting²^ORCID

Affiliation:

1. Department of Electrical Engineering, Miin Wu School of Computing, National Cheng Kung University, Tainan, Taiwan

2. Department of Electrical Engineering, Institute of Computer and Communication Engineering, National Cheng Kung University, Tainan, Taiwan

Funder

EINSTEIN Program of the National Science and Technology Council (NSTC), Taiwan

Emerging Young Scholar Program of NSTC

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/36/10354519/10493051.pdf?arnumber=10493051

Reference68 articles.

1. Hyperspectral Image Fusion

2. Hyperspectral Data Exploitation

3. A Convex Optimization-Based Coupled Nonnegative Matrix Factorization Algorithm for Hyperspectral and Multispectral Data Fusion

4. Hyperspectral Pansharpening: A Review

5. Challenges and Opportunities of Multimodality and Data Fusion in Remote Sensing

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