Spatial resolution enhancement techniques of space-borne microwave radiometer

2014 ◽  
Author(s):  
Yu Sun ◽  
Xiangxin Meng ◽  
Weidong Hu ◽  
Xin Lv
Keyword(s):  
Spatial Resolution ◽  
Microwave Radiometer ◽  
Resolution Enhancement

On the Spatial Resolution Enhancement of Microwave Radiometer Data in Banach Spaces

2014 ◽  
Vol 52 (3) ◽  
pp. 1834-1842 ◽  
Author(s):  
Flavia Lenti ◽  
Ferdinando Nunziata ◽  
Claudio Estatico ◽  
Maurizio Migliaccio
Keyword(s):  
Banach Spaces ◽  
Spatial Resolution ◽  
Microwave Radiometer ◽  
Resolution Enhancement

scholarly journals Spatial Resolution Enhancement of Satellite Microwave Radiometer Data with Deep Residual Convolutional Neural Network

2019 ◽  
Vol 11 (7) ◽  
pp. 771 ◽  
Author(s):  
Weidong Hu ◽  
Yade Li ◽  
Wenlong Zhang ◽  
Shi Chen ◽  
Xin Lv ◽  
...  
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Spatial Resolution ◽  
Microwave Radiometer ◽  
Resolution Enhancement ◽  
Sampling Interval ◽  
Antenna Pattern ◽  
Degradation Factor ◽  
High Resolution Images ◽  
Satellite Microwave

Satellite microwave radiometer data is affected by many degradation factors during the imaging process, such as the sampling interval, antenna pattern and scan mode, etc., leading to spatial resolution reduction. In this paper, a deep residual convolutional neural network (CNN) is proposed to solve these degradation problems by learning the end-to-end mapping between low-and high-resolution images. Unlike traditional methods that handle each degradation factor separately, our network jointly learns both the sampling interval limitation and the comprehensive degeneration factors, including the antenna pattern, receiver sensitivity and scan mode, during the training process. Moreover, due to the powerful mapping capability of the deep residual CNN, our method achieves better resolution enhancement results both quantitatively and qualitatively than the methods in literature. The microwave radiation imager (MWRI) data from the Fengyun-3C (FY-3C) satellite has been used to demonstrate the validity and the effectiveness of the method.

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