Hyperspectral Image Denoising Via Nonlocal Rank Residual Modeling-Reference-Cited by-同舟云学术

Hyperspectral Image Denoising Via Nonlocal Rank Residual Modeling

Published:2023-06-04 Issue: Volume: Page:
ISSN:
Container-title:ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
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Author:

Zha Zhiyuan¹,Wen Bihan¹,Yuan Xin²,Zhou Jiantao³,Zhu Ce⁴

Affiliation:

1. Nanyang Technological University,School of Electrical & Electronic Engineering,Singapore,639798

2. Westlake University,School of Engineering,Hangzhou,China,310024

3. University of Macau,Department of Computer and Information Science,Macau,China,999078

4. University of Electronic Science and Technology of China,School of Information and Communication Engineering,Chengdu,China,611731

Funder

National Natural Science Foundation of China

Science and Technology Development Fund

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10094559/10094560/10096242.pdf?arnumber=10096242

Reference32 articles.

1. Non-local meets global: An iterative paradigm for hyperspectral im-age restoration;he;IEEE Transactions on Pattern Analysis and Machine Intelligence,2022

2. MAC-Net: Model Aided Nonlocal Neural Network for Hyperspectral Image Denoising

3. Kronecker-Basis-Representation Based Tensor Sparsity and Its Applications to Tensor Recovery

4. Robust Tensor Approximation With Laplacian Scale Mixture Modeling for Multiframe Image and Video Denoising

5. Image quality assessment: from error visibility to structural similarity;zhou;IEEE Transactions on Image Processing,2004

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