SGDFormer: One-stage transformer-based architecture for cross-spectral stereo image guided denoising-Reference-Cited by-同舟云学术

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SGDFormer: One-stage transformer-based architecture for cross-spectral stereo image guided denoising

Published:2025-01 Issue: Volume:113 Page:102603
ISSN:1566-2535
Container-title:Information Fusion
language:en
Short-container-title:Information Fusion

Author:

Zhang Runmin,Yu Zhu,Sheng Zehua,Ying Jiacheng,Cao Si-Yuan,Chen Shu-Jie,Yang Bailin,Li Junwei,Shen Hui-Liang^ORCID

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Ministry of Science and Technology of the People's Republic of China

Natural Science Foundation of Zhejiang Province

Jinhua Science and Technology Bureau

Publisher

Elsevier BV

Reference70 articles.

1. Image denoising review: from classical to state-of-the-art approaches;Goyal;Inf. Fusion,2020

2. Beyond a Gaussian denoiser: Residual learning of deep CNN for image denoising;Zhang;IEEE Trans. Image Process.,2017

3. S.W. Zamir, A. Arora, S. Khan, M. Hayat, F.S. Khan, M.-H. Yang, L. Shao, Multi-stage progressive image restoration, in: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2021, pp. 14821–14831.

4. L. Chen, X. Chu, X. Zhang, J. Sun, Simple baselines for image restoration, in: Proceedings of the European Conference on Computer Vision, 2022, pp. 17–33.

5. Y. Jiang, B. Wronski, B. Mildenhall, J.T. Barron, Z. Wang, T. Xue, Fast and high quality image denoising via malleable convolution, in: Proceedings of the European Conference on Computer Vision, 2022, pp. 429–446.

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