College of Information Science and Engineering
Henan University of Technology
China
Homepage
School of Information Science and Engineering
Henan University of Technology
China
Homepage
School of Artificial Intelligence and Big Data
Henan University of Technology
China
Homepage
School of Artificial Intelligence and Big Data
Henan University of Technology
China
Homepage
School of Information Science and Engineering
Henan University of Technology
China
Homepage1. Wang, Yulei, Xi Chen, Fengchao Wang, Meiping Song, and Chunyan Yu, "Meta-learning based hyperspectral target detection using Siamese network," IEEE Transactions on Geoscience and Remote Sensing, Vol. 60, 1-13, 2022.
2. Liu, Chun, Longwei Yang, Zheng Li, Wei Yang, Zhigang Han, Jianzhong Guo, and Junyong Yu, "Multi-level relation learning for cross-domain few-shot hyperspectral image classification," Applied Intelligence, Vol. 54, No. 5, 4392-4410, 2024.
3. Ma, Zhenyu and Bin Yang, "Spatial-spectral hypergraph-based unsupervised band selection for hyperspectral remote sensing images," IEEE Sensors Journal, Vol. 24, No. 17, 27870-27882, 2024.
4. Qu, Xiaorui, Jufeng Zhao, Yanhui Cheng, Haijun Tian, and Guangmang Cui, "Compressed hyperspectral imaging based on residual-spectral attention mechanism and similar image prior," Optics and Lasers in Engineering, Vol. 180, 108330, 2024.
5. Rasti, Behnood, Paul Scheunders, Pedram Ghamisi, Giorgio Licciardi, and Jocelyn Chanussot, "Noise reduction in hyperspectral imagery: Overview and application," Remote Sensing, Vol. 10, No. 3, 482, 2018.
6. Zhang, Qiang, Qiangqiang Yuan, Jie Li, Xinxin Liu, Huanfeng Shen, and Liangpei Zhang, "Hybrid noise removal in hyperspectral imagery with a spatial–spectral gradient network," IEEE Transactions on Geoscience and Remote Sensing, Vol. 57, No. 10, 7317-7329, 2019.
7. Bahraini, Tahereh, Abbas Ebrahimi-Moghadam, Morteza Khademi, and Hadi Sadoghi Yazdi, "Bayesian framework selection for hyperspectral image denoising," Signal Processing, Vol. 201, 108712, 2022.
8. Li, Heng-Chao, Xin-Ru Feng, Rui Wang, Lianru Gao, and Qian Du, "Superpixel-based low-rank tensor factorization for blind nonlinear hyperspectral unmixing," IEEE Sensors Journal, Vol. 24, No. 8, 13055-13072, 2024.
9. Fu, Hang, Genyun Sun, Aizhu Zhang, Baojie Shao, Jinchang Ren, and Xiuping Jia, "Tensor singular spectrum analysis for 3-D feature extraction in hyperspectral images," IEEE Transactions on Geoscience and Remote Sensing, Vol. 61, 1-14, 2023.
10. Wang, Zhicheng, Michael K. Ng, Lina Zhuang, Lianru Gao, and Bing Zhang, "Nonlocal self-similarity-based hyperspectral remote sensing image denoising with 3-D convolutional neural network," IEEE Transactions on Geoscience and Remote Sensing, Vol. 60, 1-17, 2022.
11. He, Chengxun, Le Sun, Wei Huang, Jianwei Zhang, Yuhui Zheng, and Byeungwoo Jeon, "TSLRLN: Tensor subspace low-rank learning with non-local prior for hyperspectral image mixed denoising," Signal Processing, Vol. 184, 108060, 2021.
12. Maggioni, Matteo, Vladimir Katkovnik, Karen Egiazarian, and Alessandro Foi, "Nonlocal transform-domain filter for volumetric data denoising and reconstruction," IEEE Transactions on Image Processing, Vol. 22, No. 1, 119-133, 2013.
13. Peng, Jiangtao, Weiwei Sun, Heng-Chao Li, Wei Li, Xiangchao Meng, Chiru Ge, and Qian Du, "Low-rank and sparse representation for hyperspectral image processing: A review," IEEE Geoscience and Remote Sensing Magazine, Vol. 10, No. 1, 10-43, 2021.
14. Gong, Xiao, Wei Chen, and Jie Chen, "A low-rank tensor dictionary learning method for hyperspectral image denoising," IEEE Transactions on Signal Processing, Vol. 68, 1168-1180, 2020.
15. Zhang, Feng, Kai Zhang, Wenbo Wan, and Jiande Sun, "3D geometrical total variation regularized low-rank matrix factorization for hyperspectral image denoising," Signal Processing, Vol. 207, 108942, 2023.
16. Murugesan, Ramya, Nandhagopal Nachimuthu, and G. Prakash, "Attention based deep convolutional U-Net with CSA optimization for hyperspectral image denoising," Infrared Physics & Technology, Vol. 129, 104531, 2023.
17. Fu, Hang, Ziyan Ling, Genyun Sun, Jinchang Ren, Aizhu Zhang, Li Zhang, and Xiuping Jia, "HyperDehazing: A hyperspectral image dehazing benchmark dataset and a deep learning model for haze removal," ISPRS Journal of Photogrammetry and Remote Sensing, Vol. 218, 663-677, 2024.
18. Sun, Le, Qiujie Cao, Yuwen Chen, Yuhui Zheng, and Zebin Wu, "Mixed noise removal for hyperspectral images based on global tensor low-rankness and nonlocal SVD-aided group sparsity," IEEE Transactions on Geoscience and Remote Sensing, Vol. 61, 1-17, 2023.
19. Chang, Yi, Luxin Yan, Houzhang Fang, Sheng Zhong, and Wenshan Liao, "HSI-DeNet: Hyperspectral image restoration via convolutional neural network," IEEE Transactions on Geoscience and Remote Sensing, Vol. 57, No. 2, 667-682, 2018.
20. Nguyen, Han V., Magnus O. Ulfarsson, Jakob Sigurdsson, and Johannes R. Sveinsson, "Deep sparse and low-rank prior for hyperspectral image denoising," IGARSS 2022 --- 2022 IEEE International Geoscience and Remote Sensing Symposium, 1217-1220, Kuala Lumpur, Malaysia, 2022.
21. Do, T. and T. Vetterli, "Wavelet-based denoising methods: A review," IEEE Signal Processing Magazine, Vol. 22, No. 6, 84-93, 2005.
22. Zhang, Qiang, Qiangqiang Yuan, Jie Li, Xinxin Liu, Huanfeng Shen, and Liangpei Zhang, "Hybrid noise removal in hyperspectral imagery with a spatial-spectral gradient network," IEEE Transactions on Geoscience and Remote Sensing, Vol. 57, No. 10, 7317-7329, 2019.
23. Wang, Siqi, Liyuan Li, Xiaoyan Li, Jingwen Zhang, Lixing Zhao, Xiaofeng Su, and Fansheng Chen, "A denoising network based on frequency-spectral-spatial-feature for hyperspectral image," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol. 16, 6693-6710, 2023.
24. Dusmanu, Mihai, Ignacio Rocco, Tomas Pajdla, Marc Pollefeys, Josef Sivic, Akihiko Torii, and Torsten Sattler, "D2-net: A trainable cnn for joint description and detection of local features," Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 8092-8101, 2019.
25. Pan, Erting, Yong Ma, Xiaoguang Mei, Fan Fan, Jun Huang, and Jiayi Ma, "SQAD: Spatial-spectral quasi-attention recurrent network for hyperspectral image denoising," IEEE Transactions on Geoscience and Remote Sensing, Vol. 60, 1-14, 2022.
26. Yuan, Qiangqiang, Qiang Zhang, Jie Li, Huanfeng Shen, and Liangpei Zhang, "Hyperspectral image denoising employing a spatial-spectral deep residual convolutional neural network," IEEE Transactions on Geoscience and Remote Sensing, Vol. 57, No. 2, 1205-1218, 2018.
27. Carion, Nicolas, Francisco Massa, Gabriel Synnaeve, Nicolas Usunier, Alexander Kirillov, and Sergey Zagoruyko, "End-to-end object detection with transformers," European Conference on Computer Vision, 213-229, Springer International Publishing, Cham, 2020.
28. Wang, Mengyuan, Wei He, and Hongyan Zhang, "A spatial-spectral transformer network with total variation loss for hyperspectral image denoising," IEEE Geoscience and Remote Sensing Letters, Vol. 20, 5503105, 2023.
29. Lai, Zeqiang, Chenggang Yan, and Ying Fu, "Hybrid spectral denoising transformer with guided attention," Proceedings of the IEEE/CVF International Conference on Computer Vision, 13065-13075, Paris, France, 2023.
30. Li, Miaoyu, Ying Fu, and Yulun Zhang, "Spatial-spectral transformer for hyperspectral image denoising," Proceedings of the AAAI Conference on Artificial Intelligence, Vol. 37, No. 1, 1368-1376, Washington, USA, 2023.
31. Sun, Le, Xinyu Wang, Yuhui Zheng, Zebin Wu, and Liyong Fu, "Multiscale 3-D-2-D mixed CNN and lightweight attention-free transformer for hyperspectral and LiDAR classification," IEEE Transactions on Geoscience and Remote Sensing, Vol. 62, 2100116, 2024.
32. Hu, Shuai, Feng Gao, Xiaowei Zhou, Junyu Dong, and Qian Du, "Hybrid convolutional and attention network for hyperspectral image denoising," IEEE Geoscience and Remote Sensing Letters, Vol. 21, 5504005, 2024.
33. Xiong, Fengchao, Jun Zhou, Qinling Zhao, Jianfeng Lu, and Yuntao Qian, "MAC-Net: Model-aided nonlocal neural network for hyperspectral image denoising," IEEE Transactions on Geoscience and Remote Sensing, Vol. 60, 1-14, 2021.
34. Wang, Di, Jing Zhang, Bo Du, Liangpei Zhang, and Dacheng Tao, "DCN-T: Dual context network with transformer for hyperspectral image classification," IEEE Transactions on Image Processing, Vol. 32, 2536-2551, 2023.
35. Xue, Xizhe, Haokui Zhang, Bei Fang, Zongwen Bai, and Ying Li, "Grafting transformer on automatically designed convolutional neural network for hyperspectral image classification," IEEE Transactions on Geoscience and Remote Sensing, Vol. 60, 1-16, 2022.
36. Bodrito, T., Alexandre Zouaoui, Jocelyn Chanussot, and Julien Mairal, "A trainable spectral-spatial sparse coding model for hyperspectral image restoration," Advances in Neural Information Processing Systems, Vol. 34, 5430-5442, 2021.
37. Kalman, Linda S. and Edward M. Bassett III, "Classification and material identification in an urban environment using HYDICE hyperspectral data," Imaging Spectrometry III, Vol. 3118, 57-68, San Diego, CA, United States, 1997.
38. Aharon, M., M. Elad, and A. Bruckstein, "K-SVD: An algorithm for designing overcomplete dictionaries for sparse representation," IEEE Transactions on Signal Processing, Vol. 54, No. 11, 4311-4322, 2006.
