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An attention mechanism based convolutional network for satellite precipitation downscaling over China
Yinghong Jing, Liupeng Lin, Xinghua Li +2
Precipitation is a key part of hydrological circulation and is a sensitive indicator of climate change. The Integrated Multi-satellitE Retrievals for the Global Precipitation Measu…
An Urban Water Extraction Method Combining Deep Learning and Google Earth Engine
Yudie Wang, Zhiwei Li, Chao Zeng +2
Urban water is important for the urban ecosystem. Accurate and efficient detection of urban water with remote sensing data is of great significance for urban management and plannin…
Deep learning based cloud detection for medium and high resolution remote sensing images of different sensors
Zhiwei Li, Huanfeng Shen, Qing Cheng +3
Cloud detection is an important preprocessing step for the precise application of optical satellite imagery. In this paper, we propose a deep learning based cloud detection method…
Hybrid Noise Removal in Hyperspectral Imagery With a Spatial-Spectral Gradient Network
Qiang Zhang, Qiangqiang Yuan, Jie Li +3
The existence of hybrid noise in hyperspectral images (HSIs) severely degrades the data quality, reduces the interpretation accuracy of HSIs, and restricts the subsequent HSIs appl…
Oblique Stripe Removal in Remote Sensing Images via Oriented Variation
Xinxin Liu, Xiliang Lu, Huanfeng Shen +2
Destriping is a classical problem in remote sensing image processing. Although considerable effort has been made to remove stripes, few of the existing methods can eliminate stripe…
Spatial-Spectral Fusion by Combining Deep Learning and Variation Model
Huanfeng Shen, Menghui Jiang, Jie Li +3
In the field of spatial-spectral fusion, the model-based method and the deep learning (DL)-based method are state-of-the-art. This paper presents a fusion method that incorporates…
Land-Cover Classification with High-Resolution Remote Sensing Images Using Transferable Deep Models
Xin-Yi Tong, Gui-Song Xia, Qikai Lu +4
In recent years, large amount of high spatial-resolution remote sensing (HRRS) images are available for land-cover mapping. However, due to the complex information brought by the i…
Hyperspectral Image Denoising Employing a Spatial-Spectral Deep Residual Convolutional Neural Network
Qiangqiang Yuan, Qiang Zhang, Jie Li +2
Hyperspectral image (HSI) denoising is a crucial preprocessing procedure to improve the performance of the subsequent HSI interpretation and applications. In this paper, a novel de…
A Multi-Scale and Multi-Depth Convolutional Neural Network for Remote Sensing Imagery Pan-Sharpening
Qiangqiang Yuan, Yancong Wei, Xiangchao Meng +2
Pan-sharpening is a fundamental and significant task in the field of remote sensing imagery processing, in which high-resolution spatial details from panchromatic images are employ…
Correction of "Cloud Removal By Fusing Multi-Source and Multi-Temporal Images"
Chengyue Zhang, Zhiwei Li, Qing Cheng +2
Remote sensing images often suffer from cloud cover. Cloud removal is required in many applications of remote sensing images. Multitemporal-based methods are popular and effective…
Boosting the accuracy of multi-spectral image pan-sharpening by learning a deep residual network
Yancong Wei, Qiangqiang Yuan, Huanfeng Shen +1
In the field of fusing multi-spectral and panchromatic images (Pan-sharpening), the impressive effectiveness of deep neural networks has been recently employed to overcome the draw…
A Spatial and Temporal Non-Local Filter Based Data Fusion
Qing Cheng, Huiqing Liu, Huanfeng Shen +2
The trade-off in remote sensing instruments that balances the spatial resolution and temporal frequency limits our capacity to monitor spatial and temporal dynamics effectively. Th…
Multi-feature combined cloud and cloud shadow detection in GaoFen-1 wide field of view imagery
Zhiwei Li, Huanfeng Shen, Huifang Li +3
The wide field of view (WFV) imaging system onboard the Chinese GaoFen-1 (GF-1) optical satellite has a 16-m resolution and four-day revisit cycle for large-scale Earth observation…