1k citations · 4.6k across the 34 of their papers we have counts for
6 papers · 2 filters
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…