Image super-resolution network model and reconstruction method

The invention discloses an image super-resolution network model and a reconstruction method, and the method comprises the following steps: obtaining a low-resolution image obtained by carrying out the down-sampling of an original high-resolution image, and carrying out the feature extraction of the low-resolution image, so as to obtain an initial feature map; processing the initial feature map by using a preset up-sampling method to obtain a super-resolution image; constructing an L1 loss function based on the original high-resolution image and the super-resolution image; using the L1 loss function to train the MCRAN network so as to obtain a trained MCRAN network model; and inputting a low-resolution image to be optimized into the trained MCRAN network model to obtain a corresponding super-resolution image. According to the method, the performance of the super-resolution network is improved by using the MCRAN network, and the visual quality of the image super-resolution is improved. 本发明公开了一种图像超分辨率网络模型和重建方法，所