525 citations · 2.9k across the 23 of their papers we have counts for
10 papers · 1 filter
Deep Blind Super-Resolution for Satellite Video
Yi Xiao, Qiangqiang Yuan, Qiang Zhang +1
Recent efforts have witnessed remarkable progress in Satellite Video Super-Resolution (SVSR). However, most SVSR methods usually assume the degradation is fixed and known, e.g., bi…
Local-Global Temporal Difference Learning for Satellite Video Super-Resolution
Yi Xiao, Qiangqiang Yuan, Kui Jiang +4
Optical-flow-based and kernel-based approaches have been extensively explored for temporal compensation in satellite Video Super-Resolution (VSR). However, these techniques are les…
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…
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…
Missing Data Reconstruction in Remote Sensing image with a Unified Spatial-Temporal-Spectral Deep Convolutional Neural Network
Qiang Zhang, Qiangqiang Yuan, Chao Zeng +2
Because of the internal malfunction of satellite sensors and poor atmospheric conditions such as thick cloud, the acquired remote sensing data often suffer from missing information…
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…
Learning a Dilated Residual Network for SAR Image Despeckling
Qiang Zhang, Qiangqiang Yuan, Jie Li +2
In this paper, to break the limit of the traditional linear models for synthetic aperture radar (SAR) image despeckling, we propose a novel deep learning approach by learning a non…
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…