Lightweight Super Resolution Reconstruction Method of Remote Sensing Image Based on Structural Reparameterization
Due to various factors in the imaging process,the resolution of the remote sensing image obtained is low and it is difficult to achieve the desired observation effect.Quality enhancement needs to be achieved with the help of super resolution reconstruction technology.In view of the fact that most of the remote sensing image super resolution reconstruction algorithms focus on improving the performance of the super separation network model,ignoring the reasoning speed is also important to the super resolution reconstruction algorithm,a remote sensing image super resolution lightweight reconstruction method based on structural re-parameterization is designed.In inferencing,the model parameters and floating-point operands are reduced by parameter equivalent transformation,so as to achieve faster inferencing speed.Experiments are carried out on AID and NWPU-RESISC45 remote sensing data sets,and the ECBASR method proposed in this paper is compared with the classical super resolution reconstruction method according to the peak signal-to-noise ratio and structural similarity of typical evaluation indicators.The experimental results show that ECBASR achieves good reconstruction performance,greatly reduces the memory occupied by operation,and speeds up the speed of inferencing.
万方数据
维普
