11 citations · 11 across the 1 of their papers we have counts for
4 papers
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…
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…
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…