Research on super-resolution reconstruction technique of SAR images based on neural network
Synthetic aperture radar(SAR)images play an important role in the fields of terrain mapping and crop phenology monitoring etc.In order to improve SAR image resolution,using the super-resolution reconstruction of SAR images supported by SRGAN,the model loading data structure is improved by use of Sentinel-1A radar satel-lite SAR images and GF-3 satellite SAR images of the same region to form the data set of training model,with the feature detail of Sentinel-1A radar satellite SAR images improved up to a level close to that of GF-3 satellite SAR image.The experiments show this method can enhance the feature detail of Sentinel-1A SAR images with the polar-isation mode of VV.
super-resolution generative adversarial networks(SRGAN)SAR imagessuper-resolution reconstruc-tion of image
国家科技期刊平台
NSTL
万方数据
维普
