Since the existing algorithm LapSRN only using the robust Charbonnier loss and traditional convolution kernel，it can cause model cannot extract more high-frequency information and have relatively small receptive filed. In this paper, we use structur- al loss combined with robust Charbonnier loss and use dilated convolution kernel to replace the traditional convolution kernel to im- prove the performance of our model. Experimental results show that our model can extract more high-frequency information and the quality of reconstructed image has been improved, meanwhile it doesn’t increase the complexity of model.