1.此处提供Hyperion高光谱遥感影像复原数据(noise_EOI.zip),相关数据介绍参见以下两篇论文，使用数据时请您引用相关论文。如您有对其它资源的需求，我们竭诚欢迎您的垂询。

• [1] H. Zhang, W. He, L. Zhang, H. Shen, Q. Yuan, "Hyperspectral Image Restoration Using Low-Rank Matrix Recovery", IEEE Transactions on Geoscience and Remote Sensing, vol. 52, no. 8, pp. 4729-4743, 2014. (ESI Hot Paper, ESI Highly Cited Paper) (PDF)
• [2] W. He, H. Zhang*, L. Zhang, H. Shen, "Total-Variation-Regularized Low-rank Matrix Factorization for Hyperspectral Image Restoration", IEEE Trans. on Geoscience and Remote Sensing, vol. 54, no. 1, pp. 178 - 188, 2016. (ESI Highly Cited Paper)(PDF)

2.此处提供云/阴影检测标注数据。由于该文件较大，无法上传，如您需要该数据，请通过邮件或其它方式联系我们。相关数据介绍参见以下论文,使用数据时请您引用相关论文。

• [1] H. Zhai, H. Zhang*, L. Zhang*, P. Li, "Cloud/Shadow Detection Framework based on Spectral Indices for Multi/Hyperspectral Optical Remote Sensing Imagery", ISPRS Journal of Photogrammetry and Remote Sensing, vol. 144, pp.235-253,2018.(PDF)

3.此处提供Gaofen-5高光谱遥感影像复原数据（下载链接1,下载链接2）。相关数据介绍参见以下论文,使用数据时请您引用相关论文。如您有对其它资源的需求，我们竭诚欢迎您的垂询。

[1] H. Zhang, H. Chen, G. Yang and L. Zhang, "LR-Net: Low-Rank Spatial-Spectral Network for Hyperspectral Image Denoising," in IEEE Transactions on Image Processing, vol. 30, pp. 8743-8758, 2021.

4.MTSOD dataset is constructed from the multi-temporal SAR-optical (Sentinel-1 and Sentinel-2) and DEM (STRM3) products, which can utilized for the research of image synthesis and cloud removal in Sentinle-2 imagery. It covers parts of Henan and Anhui provinces in China, and contains abundant landforms, including cropland, urban, barren, forest, water, and so on, which now is is avaliable at Downloaded Link.For the introduction of relevant data, please refer to the following papers, please cite the relevant papers when using the data. If you have any needs for other resources, we wholeheartedly welcome your inquiries.

[1] Y. Xia, H. Zhang*, "A deep learning-based framework for removing large-area clouds in optical imagery through the fusion of multi-temporal SAR and DEM data," preprint, 2022..