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Recent advances in All-in-One (AiO) RGB image restoration have demonstrated the effectiveness of prompt learning in handling multiple degradations within a single model.
The airborne visible/infrared imaging spectrometer (aviris)
Gregg Vane, Robert Green, Thomas Chrien, Harry Enmark, Earl Hansen, and Wallace Porter · 1993
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Hyperspectral remote sensing data analysis and future challenges
Jose M. Bioucas-Dias, Antonio Plaza, Gustavo Camps-Valls, Paul Scheunders, Nasser Nasrabadi, and Jocelyn Chanussot · 2013
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Nonlocal transform-domain filter for volumetric data denoising and reconstruction
Matteo Maggioni, Vladimir Katkovnik, Karen Egiazarian, and Alessandro Foi · 2013
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Unmixing-based denoising for destriping and inpainting of hyperspectral images
Daniele Cerra, Rupert Müller, and Peter Reinartz · 2014
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Lrtv: Mr image super-resolution with low-rank and total variation regularizations
Feng Shi, Jian Cheng, Li Wang, Pew-Thian Yap, and Dinggang Shen · 2015
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Xception: Deep learning with depthwise separable convolutions
François Chollet · 2016
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Joint anomaly detection and spectral unmixing for planetary hyperspectral images
Sina Nakhostin, Harold Clenet, Thomas Corpetti, and Nicolas Courty · 2016
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Densely connected convolutional networks
Gao Huang, Zhuang Liu, Laurens Van Der Maaten, and Kilian Q. Weinberger · 2017
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Single hyperspectral image super-resolution with grouped deep recursive residual network
Yong Li, Lei Zhang, Chen Dingl, Wei Wei, and Yanning Zhang · 2018
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Fast hyperspectral image denoising and inpainting based on low-rank and sparse representations
Lina Zhuang and José M. Bioucas-Dias · 2018
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Non-local meets global: An integrated paradigm for hyperspectral denoising
Wei He, Quanming Yao, Chao Li, Naoto Yokoya, and Qibin Zhao · 2019
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Decoupled weight decay regularization, 2019
Ilya Loshchilov and Frank Hutter · 2019
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Deep hyperspectral prior: Single-image denoising, inpainting, super-resolution
Oleksii Sidorov and Jon Yngve Hardeberg · 2019
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Hyperspectral image denoising employing a spatial–spectral deep residual convolutional neural network
Qiangqiang Yuan, Qiang Zhang, Jie Li, Huanfeng Shen, and Liangpei Zhang · 2019
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Learning spatial-spectral prior for super-resolution of hyperspectral imagery
Junjun Jiang, He Sun, Xianming Liu, and Jiayi Ma · 2020
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A new hyperspectral compressed sensing method for efficient satellite communications
Chia-Hsiang Lin, Jose M. Bioucas Dias, Tzu-Hsuan Lin, Yen-Cheng Lin, and Chi-Hung Kao · 2020
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A general decoupled learning framework for parameterized image operators
Qingnan Fan, Dongdong Chen, Lu Yuan, Gang Hua, Nenghai Yu, and Baoquan Chen · 2021
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Swinir: Image restoration using swin transformer
Jingyun Liang, Jiezhang Cao, Guolei Sun, Kai Zhang, Luc Van Gool, and Radu Timofte · 2021
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Swin transformer: Hierarchical vision transformer using shifted windows
Ze Liu, Yutong Lin, Yue Cao, Han Hu, Yixuan Wei, Zheng Zhang, Stephen Lin, and Baining Guo · 2021
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Learning transferable visual models from natural language supervision
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, et al · 2021
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Hyperspectral image denoising with realistic data
Tao Zhang, Ying Fu, and Cheng Li · 2021
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Satellitecloudgenerator: Controllable cloud and shadow synthesis for multi-spectral optical satellite images
Mikolaj Czerkawski, Robert Atkinson, Craig Michie, and Christos Tachtatzis · 2023
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Robust hyperspectral inpainting via low-rank regularized untrained convolutional neural network
Keivan Faghih Niresi and Chong-Yung Chi · 2023
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Spectral super-resolution meets deep learning: Achievements and challenges
Jiang He, Qiangqiang Yuan, Jie Li, Yi Xiao, Denghong Liu, Huanfeng Shen, and Liangpei Zhang · 2023
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Promptir: Prompting for all-in-one image restoration
Vaishnav Potlapalli, Syed Waqas Zamir, Salman Khan, and Fahad Khan · 2023
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Aacnet: Asymmetric attention convolution network for hyperspectral image dehazing
Meng Xu, Yanxin Peng, Ying Zhang, Xiuping Jia, and Sen Jia · 2023
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Deep plug-and-play prior for hyperspectral image restoration
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All-In-One Image Restoration for Unknown Corruption
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Fast reconstruction of hyperspectral image from its rgb counterpart using admm-adam theory
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A spectral grouping-based deep learning model for haze removal of hyperspectral images
Xiaofeng Ma, Qunming Wang, and Xiaohua Tong · 2022
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Fast noise removal in hyperspectral images via representative coefficient total variation
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Cloud mask intercomparison exercise (cmix): An evaluation of cloud masking algorithms for landsat 8 and sentinel-2
Sergii et al. Skakun · 2022
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Text-if: Leveraging semantic text guidance for degradation-aware and interactive image fusion
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