An Unsupervised Dehazing Network With Hybrid Prior Constraints for Hyperspectral Image-Reference-Cited by-同舟云学术

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An Unsupervised Dehazing Network With Hybrid Prior Constraints for Hyperspectral Image

Published:2024 Issue: Volume:62 Page:1-15
ISSN:0196-2892
Container-title:IEEE Transactions on Geoscience and Remote Sensing
language:
Short-container-title:IEEE Trans. Geosci. Remote Sensing

Author:

He Wei¹^ORCID,Wang Mengyuan¹^ORCID,Chen Yong²^ORCID,Zhang Hongyan³^ORCID

Affiliation:

1. State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, China

2. School of Computer and Information Engineering, Jiangxi Normal University, Nanchang, China

3. School of Computer, China University of Geosciences, Wuhan, China

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Natural Science Foundation of Jiangxi, China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/36/10354519/10497613.pdf?arnumber=10497613

Reference57 articles.

1. The use of hyperspectral remote sensing for mineral exploration: a review

2. Hyperspectral Imaging in Environmental Monitoring: A Review of Recent Developments and Technological Advances in Compact Field Deployable Systems

3. An assessment of independent component analysis for detection of military targets from hyperspectral images

4. Hyperspectral Compressive Snapshot Reconstruction via Coupled Low-Rank Subspace Representation and Self-Supervised Deep Network

5. Thick Cloud Removal in Multitemporal Remote Sensing Images via Low-Rank Regularized Self-Supervised Network

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1. An interpretable and flexible fusion prior to boost hyperspectral imaging reconstruction;Information Fusion;2024-11

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