HFAN: High-Frequency Attention Network for hyperspectral image denoising-Reference-Cited by-同舟云学术

HFAN: High-Frequency Attention Network for hyperspectral image denoising

Published:2023-08-25 Issue: Volume: Page:
ISSN:1868-8071
Container-title:International Journal of Machine Learning and Cybernetics
language:en
Short-container-title:Int. J. Mach. Learn. & Cyber.

Author:

Yang Chuansheng,Zhang Chao,Shen Haozhen,Peng Tong,Wang Chao^ORCID,Deng Liangjian,Chen Hongming,He Liangtian

Funder

Basic Public Welfare Research Program of Zhejiang Province

Natural Science Research Project of Anhui Universities

Natural Science Foundation of Anhui Province

Key Technologies Research and Development Program

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Software

Link

https://link.springer.com/content/pdf/10.1007/s13042-023-01942-2.pdf

Reference65 articles.

1. Aggarwal HK, Majumdar A (2015) Mixed gaussian and impulse denoising of hyperspectral images. In: 2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), IEEE, pp 429–432

2. Arad B, Ben-Shahar O (2016) Sparse recovery of hyperspectral signal from natural rgb images. In: European Conference on Computer Vision, Springer, pp 19–34

3. Buades A, Coll B, Morel JM (2005) A non-local algorithm for image denoising. In: 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR’05), IEEE, pp 60–65

4. Cao X, Yao J, Xu Z et al (2020) Hyperspectral image classification with convolutional neural network and active learning. IEEE Trans Geosci Remote Sens 58(7):4604–4616

5. Cao X, Fu X, Xu C et al (2021) Deep spatial-spectral global reasoning network for hyperspectral image denoising. IEEE Trans Geosci Remote Sens 60:1–14

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