NL3DLogTNN: An Effective Hyperspectral Image Denoising Method Combined Non-Local Self-Similarity and Low-Fibered- Rank Regularization-Reference-Cited by-同舟云学术

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NL3DLogTNN: An Effective Hyperspectral Image Denoising Method Combined Non-Local Self-Similarity and Low-Fibered- Rank Regularization

Published:2023 Issue: Volume:11 Page:91082-91099
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Liu Haoran¹^ORCID,Su Tianyu²^ORCID,Du Xinzhe³^ORCID,Zhai Yuxin⁴^ORCID,Zhao Jianli²^ORCID

Affiliation:

1. College of Mechanical and Electronic, Shandong University of Science and Technology, Qingdao, China

2. College of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao, China

3. College of Electrical Engineering and Automation, Shandong University of Science and Technology, Qingdao, China

4. College of Transportation, Shandong University of Science and Technology, Qingdao, China

Funder

Shandong Provincial Natural Science Foundation Major Program

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/10005208/10214274.pdf?arnumber=10214274

Reference45 articles.

1. Coupled Sparse Denoising and Unmixing With Low-Rank Constraint for Hyperspectral Image

2. Denoising of Multispectral Images via Nonlocal Groupwise Spectrum-PCA

3. Hyperspectral image denoising with bilinear low rank matrix factorization

4. Nonlocal Transform-Domain Filter for Volumetric Data Denoising and Reconstruction

5. A Tensor Subspace Representation-Based Method for Hyperspectral Image Denoising

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1. SSCDN: a spatial-spectral collaborative network for hyperspectral image denoising;Optics Express;2024-08-26

2. An Improved Plug and Play Tensor Fiber Rank Constrained Hyperspectral Image Restoration;Advances in Applied Mathematics;2024

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