Super Resolution for Remote Sensing Images via Improved Residual Network

According to the processing characteristics of remote sensing image super-resolution, this paper studies a super resolution method based on improved residual network. First, we optimize the structure of the residual block to meet the needs of super-resolution tasks; then, we further deepen the network level, so that the network has a stronger learning ability. The reconstruction results on the remote sensing images dataset show that the improved residual network achieves better visual effect, and the objective evaluation index is significantly improved, which proves the effectiveness of the proposed method.